Abstract
Scheduling problems occurring in parallel machines manufacturing environments are quite usual and many different methods have been applied for solving it. These methods vary from the application of more or less simple heuristics and rules up to more complex methods, including distinct kind of metaheuristics. In this paper we discuss a fuzzy optimization method using simulated annealing (Fuzzy-SA) for solving an unrelated parallel machines manufacturing scheduling problem. To demonstrate the potential of our method we use an illustrative example of a parallel machines scheduling (PMS) problem and then we analyse it and perform statistical tests with 20 instances.

Abstract
In an embedded system, functions often operate under different requirements. In the extreme, a failing safety critical function may cause collateral damage (and hence consider to be a system failure) while non critical functions affect only the quality of service. Approaches by partitioning the system's functions into sandboxes require virtualization mechanisms by the underlying platform and thus prohibit deployment to the bulk of microcontroller based systems. In this paper we discuss an alternative approach based on static semantic analysis performed directly on the system specification expressed in the form of an object oriented (00) model in the experimental language RTFM-lang. This would allow to (at compile time) to discriminate in between critical and non-critical functions, and assign these (by means of statically checkable typing rules) appropriate access rights. In particular, one can imagine dynamic memory allocations to be allowed only in non-critical functions, while on the other hand, direct interaction with the environment may be restricted to the critical parts. With respect to scheduling, a static task and resource configuration allows e.g. Stack Resource Policy (SRP) based approaches to be deployed. In this paper we discuss how this can be achieved in a mixed critical setting.

Abstract
Computational systems operating in open, dynamic and decentralized environments are required to share data with previously unknown computational systems. Due to this ill specification and emergent operation the systems are required to share the data's respective schemas and semantics so that the systems can correctly manipulate, understand and reason upon the shared data. The schemas and semantics are typically provided by ontologies using specific semantics provided by the ontology language. Because computational systems adopt different ontologies to describe their domain of discourse, a consistent and compatible communication relies on the ability to reconcile (in run-time) the vocabulary used in their ontologies. Since each computational system might have its own perspective about what are the best correspondences between the adopted ontologies, conflicts can arise. To address such conflicts, computational systems may engage in any kind of negotiation process that is able to lead them to a common and acceptable agreement. This paper proposes an argumentation-based approach where the computational entities describe their own arguments according to a commonly agreed argumentation meta-model. In order to support autonomy and conceptual differences, the community argumentation model can be individually extended yet maintaining computational effectiveness. Based on the formal specification, a software development framework is proposed.

Abstract
In this article, we review the state-of-the-art techniques in mining data streams for mobile and ubiquitous environments. We start the review with a concise background of data stream processing, presenting the building blocks for mining data streams. In a wide range of applications, data streams are required to be processed on small ubiquitous devices like smartphones and sensor devices. Mobile and ubiquitous data mining target these applications with tailored techniques and approaches addressing scarcity of resources and mobility issues. Two categories can be identified for mobile and ubiquitous mining of streaming data: single-node and distributed. This survey will cover both categories. Mining mobile and ubiquitous data require algorithms with the ability to monitor and adapt the working conditions to the available computational resources. We identify the key characteristics of these algorithms and present illustrative applications. Distributed data stream mining in the mobile environment is then discussed, presenting the Pocket Data Mining framework. Mobility of users stimulates the adoption of context-awareness in this area of research. Context-awareness and collaboration are discussed in the Collaborative Data Stream Mining, where agents share knowledge to learn adaptive accurate models. Conflict of interest: The authors have declared no conflicts of interest for this article. For further resources related to this article, please visit the .

Abstract

Abstract
To analyze the simultaneous effects of sociodemographic variables and time on each food group contribution to total Portuguese elderly household food availability. Four cross sectional Portuguese Household Budget Surveys were used. A multivariate analysis of variance (MANOVA), using a general linear model (GLM), was applied to analyze the simultaneous effects of sociodemographic variables and time. Portuguese population. Nationally representative samples of households with members aged a parts per thousand yen 65 years were selected and categorized as solitary elderly female, solitary elderly male, or couple (one elderly female and one elderly male). Samples included 1,967 households in 1989-1990, 2,219 households in 1994-1995, 2,533 households in 2000-2001 and 2,441 households in 2005-2006. The simultaneous effects of sociodemographic variables and time were significant for all food groups (P < 0.001). The highest contribution for the total household food availability was found for cereals, potatoes, alcoholic beverages, nonalcoholic beverages and fruits. The effects were large for "household food availability" and medium for "elderly household type", "urbanization degree", "income", "food expenses" and "eating out expenses". Solitary elderly male households had the highest proportion of cereals and alcoholic beverages, whilst solitary elderly female households had higher availability of milk/milk products and fruits. Households located in urban areas had higher contribution of milk/milk products while rural, had higher contribution of potatoes. The simultaneous effect of the studied variables on food group contribution to total household food availability can be considered when addressing dietary recommendation for providing an insight into the motivations associated with food purchases.