Agent-based Content Retrieval for Opportunistic Content-Centric Networks

In this paper, we describe agent-based content retrieval for opportunistic networks, where requesters can delegate content retrieval to agents, which retrieve the content on their behalf. The approach has been implemented in CCNx, the open source CCN framework, and evaluated on Android smart phones. Evaluations have shown that the overhead of agent delegation is only noticeable for very small content. For content larger than 4MB, agent-based content retrieval can even result in a throughput increase of 20% compared to standard CCN download applications. The requester asks every probe interval for agents that have retrieved the desired content. Evaluations have shown that a probe interval of 30s delivers the best overall performance in our scenario because the number of transmitted notification messages can be decreased by up to 80% without significantly increasing the download time.

Viral load versus CD4⁺ monitoring and 5-year outcomes of antiretroviral therapy in HIV-positive children in Southern Africa: a cohort-based modelling study.

OBJECTIVES Many paediatric antiretroviral therapy (ART) programmes in Southern Africa rely on CD4⁺ to monitor ART. We assessed the benefit of replacing CD4⁺ by viral load monitoring. DESIGN A mathematical modelling study. METHODS A simulation model of HIV progression over 5 years in children on ART, parameterized by data from seven South African cohorts. We simulated treatment programmes with 6-monthly CD4⁺ or 6- or 12-monthly viral load monitoring. We compared mortality, second-line ART use, immunological failure and time spent on failing ART. In further analyses, we varied the rate of virological failure, and assumed that the rate is higher with CD4⁺ than with viral load monitoring. RESULTS About 7% of children were predicted to die within 5 years, independent of the monitoring strategy. Compared with CD4⁺ monitoring, 12-monthly viral load monitoring reduced the 5-year risk of immunological failure from 1.6 to 1.0% and the mean time spent on failing ART from 6.6 to 3.6 months; 1% of children with CD4⁺ compared with 12% with viral load monitoring switched to second-line ART. Differences became larger when assuming higher rates of virological failure. When assuming higher virological failure rates with CD4⁺ than with viral load monitoring, up to 4.2% of children with CD4⁺ compared with 1.5% with viral load monitoring experienced immunological failure; the mean time spent on failing ART was 27.3 months with CD4⁺ monitoring and 6.0 months with viral load monitoring. Conclusion: Viral load monitoring did not affect 5-year mortality, but reduced time on failing ART, improved immunological response and increased switching to second-line ART.

Agent-based model for the effect of curing temperature on cement hydration

The agent-based model presented here, comprises an algorithm that computes the degree of hydration, the water consumption and the layer thickness of C-S-H gel as functions of time for different temperatures and different w/c ratios. The results are in agreement with reported experimental studies, demonstrating the applicability of the model. As the available experimental results regarding elevated curing temperature are scarce, the model could be recalibrated in the future. Combining the agent-based computational model with TGA analysis, a semiempirical method is achieved to be used for better understanding the microstructure development in ordinary cement pastes and to predict the influence of temperature on the hydration process.

Agent Architecture Modelling at the Knowledge Level

The definition of an agent architecture at the knowledge level makes emphasis on the knowledge role played by the data interchanged between the agent components and makes explicit this data interchange this makes easier the reuse of these knowledge structures independently of the implementation This article defines a generic task model of an agent architecture and refines some of these tasks using the interference diagrams. Finally, a operationalisation of this conceptual model using the rule-oriented language Jess is shown. knowledge level,

Agent-based modeling and simulation for the design of the future european Air Traffic Management system: the experience of CASSIOPEIA

The SESAR (Single European Sky ATM Research) program is an ambitious re-search and development initiative to design the future European air traffic man-agement (ATM) system. The study of the behavior of ATM systems using agent-based modeling and simulation tools can help the development of new methods to improve their performance. This paper presents an overview of existing agent-based approaches in air transportation (paying special attention to the challenges that exist for the design of future ATM systems) and, subsequently, describes a new agent-based approach that we proposed in the CASSIOPEIA project, which was developed according to the goals of the SESAR program. In our approach, we use agent models for different ATM stakeholders, and, in contrast to previous work, our solution models new collaborative decision processes for flow traffic management, it uses an intermediate level of abstraction (useful for simulations at larger scales), and was designed to be a practical tool (open and reusable) for the development of different ATM studies. It was successfully applied in three stud-ies related to the design of future ATM systems in Europe.

An agent-based approach for the design of the future european air traffic management system

This paper describes an agent-based approach for the simulation of air traffic management (ATM) in Europe that was designed to help analyze proposals for future ATM systems. This approach is able to represent new collaborative deci-sion processes for flow traffic management, it uses an intermediate level of ab-straction (useful for simulations at larger scales), and was designed to be a practi-cal tool (open and reusable) for the development of different ATM studies. It was successfully applied in three studies related to the design of future ATM systems in Europe.

Modeling Commercial Knowledge to Develop Advanced Agent-based Marketplaces for E-commerce

This paper argues about the utility of advanced knowledge-based techniques to develop web-based applications that help consumers in finding products within marketplaces in e-commerce. In particular, we describe the idea of model-based approach to develop a shopping agent that dynamically configures a product according to the needs and preferences of customers. Finally, the paper summarizes the advantages provided by this approach.

Evaluating social choice techniques into intelligent environments by agent based social simulation

The primary hypothesis stated by this paper is that the use of social choice theory in Ambient Intelligence systems can improve significantly users satisfaction when accessing shared resources. A research methodology based on agent based social simulations is employed to support this hypothesis and to evaluate these benefits. The result is a six-fold contribution summarized as follows. Firstly, several considerable differences between this application case and the most prominent social choice application, political elections, have been found and described. Secondly, given these differences, a number of metrics to evaluate different voting systems in this scope have been proposed and formalized. Thirdly, given the presented application and the metrics proposed, the performance of a number of well known electoral systems is compared. Fourthly, as a result of the performance study, a novel voting algorithm capable of obtaining the best balance between the metrics reviewed is introduced. Fifthly, to improve the social welfare in the experiments, the voting methods are combined with cluster analysis techniques. Finally, the article is complemented by a free and open-source tool, VoteSim, which ensures not only the reproducibility of the experimental results presented, but also allows the interested reader to adapt the case study presented to different environments.

Simulazione agent-based di un sistema di m-Health per il self-management del diabete di tipo 1

L'obiettivo della tesi è dimostrare l'utilità e i vantaggi che può fornire il Self-Management del diabete mellito di tipo 1 in un sistema di mobile Health a partire da un modello computazionale Agent-Based. Viene quindi affrontata in maniera approfondita la tematica del mobile Health ed il suo sviluppo nei paesi a basso/medio reddito, illustrando i risultati ottenuti dalla ricerca scientifica fino ad oggi, ed il concetto di Self-Management di malattie croniche, un processo di cura caratterizzato dalla partecipazione autonoma del paziente stesso, fornendo una panoramica degli approcci computazionali sviluppati. Viene quindi studiato il diabete mellito in ogni sua caratteristica, seguito dall'illustrazione di diverse applicazioni per la gestione autonoma della suddetta patologia tutt'ora in commercio. Nel caso di studio vengono effettuate diverse simulazioni, tramite la piattaforma di simulazione MASON, per realizzare varie dinamiche della rete fisiologica di un paziente al fine di stabilire feedback qualitativi per il Self-Management della patologia.

The role of advanced DEM based modelling tools in increasing comminution energy efficiency

Particle breakage is an essential part of mineral processing. The aim is to reduce run of mine mineral ore to an optimal size for liberating target minerals and for subsequent recovery by separation processes such as flotation. This size reduction is typically accomplished in a series of stages in a grinding circuit tailored to the properties of the particular mine ore. Commonly this involves two or more classes of equipment starting with crushers, followed by SAG mills and then sometimes ball mills. Occasionally, high pressure grinding rolls or other novel devices are substituted. Broadly, energy consumption increases and energy efficiency decreases with the fineness of the material produced by each piece of equipment.