Probabilistic Planning in AgentSpeak using the POMDP framework.

AgentSpeak is a logic-based programming language, based on the Belief-Desire-Intention (BDI) paradigm, suitable for building complex agent-based systems. To limit the computational complexity, agents in AgentSpeak rely on a plan library to reduce the planning problem to the much simpler problem of plan selection. However, such a plan library is often inadequate when an agent is situated in an uncertain environment. In this paper, we propose the AgentSpeak+ framework, which extends AgentSpeak with a mechanism for probabilistic planning. The beliefs of an AgentSpeak+ agent are represented using epistemic states to allow an agent to reason about its uncertain observations and the uncertain effects of its actions. Each epistemic state consists of a POMDP, used to encode the agent’s knowledge of the environment, and its associated probability distribution (or belief state). In addition, the POMDP is used to select the optimal actions for achieving a given goal, even when facing uncertainty.

Weathering tests of photocatalytic facade paints containing ZnO and TiO2.

The photocatalytic properties of self-cleaning acrylic paint containing TiO2 and ZnO were studied using Acid Orange 7 as a model compound. Paints were exposed to simulated weathering tests in a QUV panel. The initial photoactivity of the unweathered paints with ZnO was significantly higher. In the case of paints containing P25 the photocatalytic activity increases with weathering time, due to increasing destruction of the polymer resin and consequent exposure of the photocatalyst pigment to the Acid Orange 7 test solution. In contrast, in the case of paints containing ZnO, a decrease in photocatalytic activity is observed after weathering, due to the loss and/or photocorrosion of ZnO particles during the weathering process.

Hui and Walter's latent-class model extended to estimate diagnostic test properties from surveillance data: a latent model for latent data

Diagnostic test sensitivity and specificity are probabilistic estimates with far reaching implications for disease control, management and genetic studies. In the absence of 'gold standard' tests, traditional Bayesian latent class models may be used to assess diagnostic test accuracies through the comparison of two or more tests performed on the same groups of individuals. The aim of this study was to extend such models to estimate diagnostic test parameters and true cohort-specific prevalence, using disease surveillance data. The traditional Hui-Walter latent class methodology was extended to allow for features seen in such data, including (i) unrecorded data (i.e. data for a second test available only on a subset of the sampled population) and (ii) cohort-specific sensitivities and specificities. The model was applied with and without the modelling of conditional dependence between tests. The utility of the extended model was demonstrated through application to bovine tuberculosis surveillance data from Northern and the Republic of Ireland. Simulation coupled with re-sampling techniques, demonstrated that the extended model has good predictive power to estimate the diagnostic parameters and true herd-level prevalence from surveillance data. Our methodology can aid in the interpretation of disease surveillance data, and the results can potentially refine disease control strategies.

Repeatability and reliability of new air and water permeability tests for assessing the durability of high-performance concretes

This paper reports on the accuracy of new test methods developed to measure the air and water permeability of high-performance concretes (HPCs). Five representative HPC and one normal concrete (NC) mixtures were tested to estimate both repeatability and reliability of the proposed methods. Repeatability acceptance was adjudged using values of signal-noise ratio (SNR) and discrimination ratio (DR), and reliability was investigated by comparing against standard laboratory-based test methods (i.e., the RILEM gas permeability test and BS EN water penetration test). With SNR and DR values satisfying recommended criteria, it was concluded that test repeatability error has no significant influence on results. In addition, the research confirmed strong positive relationships between the proposed test methods and existing standard permeability assessment techniques. Based on these findings, the proposed test methods show strong potential to become recognized as international methods for determining the permeability of HPCs.

Blood: Tests used to assess the physiological and immunological properties of blood.

The properties of blood and the relative ease of access to which it can be retrieved make it an ideal source to gauge different aspects of homeostasis within an individual, form an accurate diagnosis, and formulate an appropriate treatment regime. Tests used to determine blood parameters such as the erythrocyte sedimentation rate, hemoglobin concentration, hematocrit, bleeding and clotting times, mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration, mean cell volume, and determination of blood groups are routinely used clinically, and deviations outside the normal range can indicate a range of conditions such as anemia, pregnancy, dehydration, overhydration, infectious disease, cancer, thyroid disease, and autoimmune conditions, to mention a few. As these tests can be performed relatively inexpensively and do not require high levels of technical expertise, they are ideally suited for use in the teaching laboratory, enabling undergraduate students to link theory to practice. The practicals described here permit students to examine their own blood and that of their peers and compare these with clinically accepted normal ranges. At the end of the practicals, students are required to answer a number of questions about their findings and to link abnormal values to possible pathological conditions by answering a series of questions based on their findings.

Islanding Detection Based on Probabilistic PCA with Missing Values in PMU Data

This paper proposes a probabilistic principal component analysis (PCA) approach applied to islanding detection study based on wide area PMU data. The increasing probability of uncontrolled islanding operation, according to many power system operators, is one of the biggest concerns with a large penetration of distributed renewable generation. The traditional islanding detection methods, such as RoCoF and vector shift, are however extremely sensitive and may result in many unwanted trips. The proposed probabilistic PCA aims to improve islanding detection accuracy and reduce the risk of unwanted tripping based on PMU measurements, while addressing a practical issue on missing data. The reliability and accuracy of the proposed probabilistic PCA approach are demonstrated using real data recorded in the UK power system by the OpenPMU project. The results show that the proposed methods can detect islanding accurately, without being falsely triggered by generation trips, even in the presence of missing values.

Validity of model devices used to assess canine temperament in behavioral tests

Temperament tests are widely accepted as instruments for profiling behavioral variability in dogs, and they are applied in numerous areas of investigation (e.g. suitability for adoption or for breeding). During testing, to elicit a dog's reaction toward novel stimuli and predict its behavior in everyday life, model devices such as a child-like doll, or a fake dog, are often employed. However, the reliability of these devices to accurately stimulate dogs' reactions to children or dogs, is unknown and perhaps overestimated. This may be a particular concern in the case of aggressive behavior toward humans, a significant public health issue. The aim of this study was to: (1) evaluate the correlation between dogs' reactions to these devices, and owners' reports of their dog's aggression history (using the C-BARQ ??); (2) compare reactions toward the devices of dogs with and without histories of aggression. Subjects were selected among those visiting for behavioral consultation at the Veterinary Hospital of the University of Pennsylvania, and previously categorized as aggressive toward unfamiliar children, conspecifics, or as non-aggressive dogs (control). The test consisted of different components: an unfamiliar female tester approaching the dog; the presentation of a child-like doll, an ambiguous object, and a fake plastic dog. All tests were videotaped and durations of behaviors were later analyzed on the basis of a specified ethogram. Dogs' reactions were compared to C-BARQ scores, and interesting correlations emerged for 'dog-directed aggression/fear' (R = 0.48, P = 0.004), and 'stranger-directed aggression' (R = 0.58, P <0.001) factors. Dogs differed in their reactions toward the devices: the child-like doll and the fake dog elicited more social behaviors than the ambiguous object used as a control stimulus. Issues concerning the reliability of these tools to assess canine temperament are discussed. ?? 2012 Elsevier B.V. All rights reserved.

The value of tests in the diagnosis and management of glaucoma.

PURPOSE:

To assess the noneconomic value of tests used in the diagnosis and management of glaucoma, and explore the contexts and factors that determine such value.

DESIGN:

Perspective.

METHODS:

Selected articles from primary and secondary sources were reviewed and interpreted in the context of the authors' clinical and research experience, influenced by our perspectives on the tasks of reducing the global problem of irreversible blindness caused by glaucoma. The value of any test used in glaucoma is addressed by 3 questions regarding: its contexts, its kind of value, and its implicit or explicit benefits.

RESULTS:

Tonometry, slit-lamp gonioscopy, and optic disc evaluation remain the foundation of clinic-based case finding, whether in areas of more or less abundant resources. In resource-poor areas, there is urgency in identifying patients at risk for severe functional loss of vision; screening strategies have proven ineffective, and efforts are hindered by the inadequate allocation of support. In resource-abundant areas, the wider spectrum of glaucoma is addressed, with emphasis on early detection of structural changes of little functional consequence; these are increasingly the focus of new and expensive technologies whose clinical value has not been established in longitudinal and population-based studies. These contrasting realities in part reflect differences among the value ascribed, often implicitly, to the tests used in glaucoma.

CONCLUSIONS:

The value of any test is determined by 3 aspects: its context of usage; its comparative worth and to whom its benefit accrues; and how we define historically what we are testing. These multiple factors

Assessment of the impact speed and angle conditions for the EN1317 barrier tests

Roadside safety barriers designs are tested with passenger cars in Europe using standard EN1317 in which the impact angle for normal, high and very high containment level tests is 20°. In comparison to EN1317, the US standard MASH has higher impact angles for cars and pickups (25°) and different vehicle masses. Studies in Europe (RISER) and the US have shown values for the 90th percentile impact angle of 30°–34°. Thus, the limited evidence available suggests that the 20° angle applied in EN 1317 may be too low.
The first goal of this paper is to use the US NCHRP database (Project NCHRP 17–22) to assess the distribution of impact angle and collision speed in recent ROR accidents. Second, based on the findings of the statistical analysis and on analysis of impact angles and speeds in the literature, an LS-DYNA finite element analysis was carried out to evaluate the normal containment level of concrete barriers in non-standard collisions. The FE model was validated against a crash test of a portable concrete barrier carried out at the UK Transport Research Laboratory (TRL).
The accident data analysis for run-off road accidents indicates that a substantial proportion of accidents have an impact angle in excess of 20°. The baseline LS-DYNA model showed good comparison with experimental acceleration severity index (ASI) data and the parametric analysis indicates a very significant influence of impact angle on ASI. Accordingly, a review of European run-off road accidents and the configuration of EN 1317 should be performed.

Statistical Tests for Joint Analysis of Performance Measures

Recently there has been an increasing interest in the development of new methods using Pareto optimality to deal with multi-objective criteria (for example, accuracy and architectural complexity). Once one has learned a model based on their devised method, the problem is then how to compare it with the state of art. In machine learning, algorithms are typically evaluated by comparing their performance on different data sets by means of statistical tests. Unfortunately, the standard tests used for this purpose are not able to jointly consider performance measures. The aim of this paper is to resolve this issue by developing statistical procedures that are able to account for multiple competing measures at the same time. In particular, we develop two tests: a frequentist procedure based on the generalized likelihood-ratio test and a Bayesian procedure based on a multinomial-Dirichlet conjugate model. We further extend them by discovering conditional independences among measures to reduce the number of parameter of such models, as usually the number of studied cases is very reduced in such comparisons. Real data from a comparison among general purpose classifiers is used to show a practical application of our tests.