Context-dependent Combination of Sensor Information in Dempster-Shafer Theory for BDI

There has been much interest in the belief–desire–intention (BDI) agent-based model for developing scalable intelligent systems, e.g. using the AgentSpeak framework. However, reasoning from sensor information in these large-scale systems remains a significant challenge. For example, agents may be faced with information from heterogeneous sources which is uncertain and incomplete, while the sources themselves may be unreliable or conflicting. In order to derive meaningful conclusions, it is important that such information be correctly modelled and combined. In this paper, we choose to model uncertain sensor information in Dempster–Shafer (DS) theory. Unfortunately, as in other uncertainty theories, simple combination strategies in DS theory are often too restrictive (losing valuable information) or too permissive (resulting in ignorance). For this reason, we investigate how a context-dependent strategy originally defined for possibility theory can be adapted to DS theory. In particular, we use the notion of largely partially maximal consistent subsets (LPMCSes) to characterise the context for when to use Dempster’s original rule of combination and for when to resort to an alternative. To guide this process, we identify existing measures of similarity and conflict for finding LPMCSes along with quality of information heuristics to ensure that LPMCSes are formed around high-quality information. We then propose an intelligent sensor model for integrating this information into the AgentSpeak framework which is responsible for applying evidence propagation to construct compatible information, for performing context-dependent combination and for deriving beliefs for revising an agent’s belief base. Finally, we present a power grid scenario inspired by a real-world case study to demonstrate our work.

Electron-Impact Uncertainty Analysis and its Impact on Certain Temperature Diagnostics

In this study we calculate the electron-impact uncertainties in atomic data for direct ionization and recombination and investigate the role of these uncertainties on spectral diagnostics. We outline a systematic approach to assigning meaningful uncertainties that vary with electron temperature. Once these uncertainty parameters have been evaluated, we can then calculate the uncertainties on key diagnostics through a Monte Carlo routine, using the Astrophysical Emission Code (APEC) [Smith et al. 2001]. We incorporate these uncertainties into well known temperature diagnostics, such as the Lyman alpha versus resonance line ratio and the G ratio. We compare these calculations to a study performed by [Testa et al. 2004], where significant discrepancies in the two diagnostic ratios were observed. We conclude that while the atomic physics uncertainties play a noticeable role in the discrepancies observed by Testa, they do not explain all of them. This indicates that there is another physical process occurring in the system that is not being taken into account. This work is supported in part by the National Science Foundation REU and Department of Defense ASSURE programs under NSF Grant no. 1262851 and by the Smithsonian Institution.

Selective Multi-Carrier Index Keying OFDM: Error Propagation Rate with Moment Generating Function

We propose a new selective multi-carrier index keying in orthogonal frequency division multiplexing (OFDM) systems that opportunistically modulate both a small subset of sub-carriers and their indices. Particularly, we investigate the performance enhancement in two cases of error propagation sensitive and compromised deviceto-device (D2D) communications. For the performance evaluation, we focus on analyzing the error propagation probability (EPP) introducing the exact and upper bound expressions on the detection error probability, in the presence of both imperfect and perfect detection of active multi-carrier indices. The average EPP results in closedform are generalized for various fading distribution using the moment generating function, and our numerical results clearly show that the proposed approach is desirable for reliable and energy-efficient D2D applications.

Extravascular modified lipoproteins: a role in the propagation of diabetic retinopathy in a mouse model of type 1 diabetes

Aims/hypothesis: We aimed to determine whether plasma lipoproteins, after leakage into the retina and modification by glycation and oxidation, contribute to the development of diabetic retinopathy in a mouse model of type 1 diabetes.

Methods: To simulate permeation of plasma lipoproteins intoretinal tissues, streptozotocin-induced mouse models of diabetes and non-diabetic mice were challenged with intravitreal injection of human ‘highly-oxidised glycated’ low-density lipoprotein (HOG-LDL), native- (N-) LDL, or the vehicle PBS.Retinal histology, electroretinography (ERG) and biochemical markers were assessed over the subsequent 14 days.

Results: Intravitreal administration of N-LDL and PBS had noeffect on retinal structure or function in either diabetic or non-diabetic animals. In non-diabetic mice, HOG-LDL elicited a transient inflammatory response without altering retinal function,but in diabetic mice it caused severe, progressive retinal injury, with abnormal morphology, ERG changes, vascular leakage, vascular endothelial growth factor overexpression, gliosis, endoplasmic reticulum stress, and propensity to apoptosis.

Conclusions/interpretation: Diabetes confers susceptibility to retinal injury imposed by intravitreal injection of modified LDL. The data add to the existing evidence that extravasated, modified plasma lipoproteins contribute to the propagation of diabetic retinopathy. Intravitreal delivery of HOG-LDL simulates a stress known to be present, in addition to hyperglycaemia, in human diabetic retinopathy once blood retinal barriers are compromised.

Dealing with uncertainty: challenges and possibilities for the early childhood profession

In many countries, strategies to further develop services and institutions for the education and care of young children are linked to a discourse on professionalism. Ambitious policy goals, it is argued, can only be achieved by a skilled and qualified workforce whose practice is guided by a professional body of knowledge. This article argues that the prevailing conceptualisation of the early childhood professional is constructed out of a particular, hierarchical mode of producing and applying expert knowledge that is not necessarily appropriate to professional practice in the field of early childhood education. However, it is highly effective and contributes to forming a professional habitus that contradicts the relational core of early childhood practice. Drawing on the conceptual framework of hermeneutics, the article explores an alternative paradigm of a relational, systemic professionalism that embraces openness and uncertainty, and encourages co‐construction of professional knowledges and practices. Research, in this frame of thinking, is understood as a dialogic activity of asking critical questions and creating understandings across differences, rather than producing evidence to direct practice.

In vitro propagation of insectivorous plants for phytochemical purposes

Dissertação mest., Engenharia Biológica, Universidade do Algarve, 2009

Small area estimation for the price of habitation transaction: comparison of different uncertainty measures of temporal EBLUP

Local level planning requires statistics for small areas, but normally due to cost or logistic constraints, sample surveys are often planned to provide reliable estimates only for large geographical regions and large subgroups of a population.

Intelligent modelling of temperature propagation induced by therapeutic ultrasound

Dissertação de Mestrado, Engenharia Electrónica e Telecomunicações, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015

The generation and propagation of internal waves in Nootka Sound

senior thesis written for Oceanography 445

A simulation investigation into the effects of sea level rise on tidal propagation in fjords

Senior thesis written for Oceanography 445

Modelling the airline costs of delay propagation

Reactionary delays constitute nearly half of all delay minutes in Europe. A capped, multi-component model is presented for estimating reactionary delay costs, as a non-linear function of primary delay duration. Maximum Take-Off Weights, historically established as a charging mechanism, may be used to model delay costs. Current industry reporting on delay is flight-centric. Passenger-centric metrics are needed to better understand delay propagation. In ATM, it is important to take account of contrasting flight- and passenger-centric effects, caused by cancellations, for example. Costs to airlines and passenger disutility will both continue to be driven by delay relative to the original schedule.

The Impact of Uncertainty Shocks under Measurement Error: A Proxy SVAR approach

A growing literature considers the impact of uncertainty using SVAR models that include proxies for uncertainty shocks as endogenous variables. In this paper we consider the impact of measurement error in these proxies on the estimated impulse responses. We show via a Monte-Carlo experiment that measurement error can result in attenuation bias in impulse responses. In contrast, the proxy SVAR that uses the uncertainty shock proxy as an instrument does not su¤er from this bias. Applying this latter method to the Bloom (2009) data-set results in impulse responses to uncertainty shocks that are larger in magnitude and more persistent than those obtained from a recursive SVAR.

A risk-averse optimization model for trading wind energy in a market environment under uncertainty

In this paper, a stochastic programming approach is proposed for trading wind energy in a market environment under uncertainty. Uncertainty in the energy market prices is the main cause of high volatility of profits achieved by power producers. The volatile and intermittent nature of wind energy represents another source of uncertainty. Hence, each uncertain parameter is modeled by scenarios, where each scenario represents a plausible realization of the uncertain parameters with an associated occurrence probability. Also, an appropriate risk measurement is considered. The proposed approach is applied on a realistic case study, based on a wind farm in Portugal. Finally, conclusions are duly drawn. (C) 2011 Elsevier Ltd. All rights reserved.