Equilibrium States in Numerical Argumentation Networks

Given an argumentation network with initial values to the arguments, we look for algorithms which can yield extensions compatible with such initial values. We find that the best way of tackling this problem is to offer an iteration formula that takes the initial values and the attack relation and iterates a sequence of intermediate values that eventually converges leading to an extension. The properties surrounding the application of the iteration formula and its connection with other numerical and non-numerical techniques proposed by others are thoroughly investigated in this paper

Probabilistic Argumentation. An Equational Approach

There is a generic way to add any new feature to a system. It involves 1) identifying the basic units which build up the system and 2) introducing the new feature to each of these basic units. In the case where the system is argumentation and the feature is probabilistic we have the following. The basic units are: a. the nature of the arguments involved; b. the membership relation in the set S of arguments; c. the attack relation; and d. the choice of extensions. Generically to add a new aspect (probabilistic, or fuzzy, or temporal, etc) to an argumentation network can be done by adding this feature to each component a-d. This is a brute-force method and may yield a non-intuitive or meaningful result. A better way is to meaningfully translate the object system into another target system which does have the aspect required and then let the target system endow the aspect on the initial system. In our case we translate argumentation into classical propositional logic and get probabilistic argumentation from the translation. Of course what we get depends on how we translate. In fact, in this paper we introduce probabilistic semantics to abstract argumentation theory based on the equational approach to argumentation networks. We then compare our semantics with existing proposals in the literature including the approaches by M. Thimm and by A. Hunter. Our methodology in general is discussed in the conclusion

Percepción de la salud de los niños expresada en el lenguaje creativo de los dibujos

Objective. Children’s health perception through creative drawing language the identification of external factors perceived as negative or positive to health by children. Methodology. A descriptive study that describes the analysis of the expressive language of drawings and written comments. The sample consisted of 130 children in 3rd and 4th classes from four randomly selected schools, in the region of Central Portugal Continental (Coimbra district). The study was conducted during the first semester of 2011. The data collection was performed by means of Rodrigues’ drawing/writing sheet. This sheet is divided in 4 areas (2 of them to draw what children consider good for health and the other 2 to write the content or message of the drawings). The themes expressed are classified based on the priority areas for the promotion of healthy lifestyles. Results. children value healthy food, physical activity, mental health, prevention of inappropriate substance consumption and health and environment. The drawings and comments show links between diet and physical exercise, and between mental health and interpersonal relationships. Conclusion. Drawings and comments facilitate health professionals understanding of children’s perception of health positive and negative factors. The results of the study allow planning intervention strategies in school health from infant perception

Multi-modal Image Processing based on Coupled Dictionary Learning

In real-world scenarios, many data processing problems often involve heterogeneous images associated with different imaging modalities. Since these multimodal images originate from the same phenomenon, it is realistic to assume that they share common attributes or characteristics. In this paper, we propose a multi-modal image processing framework based on coupled dictionary learning to capture similarities and disparities between different image modalities. In particular, our framework can capture favorable structure similarities across different image modalities such as edges, corners, and other elementary primitives in a learned sparse transform domain, instead of the original pixel domain, that can be used to improve a number of image processing tasks such as denoising, inpainting, or super-resolution. Practical experiments demonstrate that incorporating multimodal information using our framework brings notable benefits.Comment: SPAWC 2018, 19th IEEE International Workshop On Signal Processing Advances In Wireless Communication

Sensitivity Analysis for a Scenario-Based Reliability Prediction Model

As a popular means for capturing behavioural requirements, scenariosshow how components interact to provide system-level functionality.If component reliability information is available, scenarioscan be used to perform early system reliability assessment. Inprevious work we presented an automated approach for predictingsoftware system reliability that extends a scenario specificationto model (1) the probability of component failure, and (2) scenariotransition probabilities. Probabilistic behaviour models ofthe system are then synthesized from the extended scenario specification.From the system behaviour model, reliability predictioncan be computed. This paper complements our previous work andpresents a sensitivity analysis that supports reasoning about howcomponent reliability and usage profiles impact on the overall systemreliability. For this purpose, we present how the system reliabilityvaries as a function of the components reliabilities and thescenario transition probabilities. Taking into account the concurrentnature of component-based software systems, we also analysethe effect of implied scenarios prevention into the sensitivity analysisof our reliability prediction technique

A model driven approach for software systems reliability

The reliability assurance of software systems from design to deployment level through transformation techniques and model driven approach, is described. Once the reliability mechanisms provided by current component-based development architectures (CBDA) are designed in a platform-independent way, platform-based design and implementation models must be extended. Current CBDAs, such as Enterprise Java Beans, address a considerable range of features to support system reliability. The evaluation aims to test maturity of the approach, its applicability, and the effectiveness of reliability models. The techniques such as process algebras are generally considered time consuming, in regard to software development