Expressiveness of Temporal Query Languages: On the Modelling of Intervals, Interval Relationships and States

Storing and retrieving time-related information are important, or even critical, tasks on many areas of Computer Science (CS) and in particular for Artificial Intelligence (AI). The expressive power of temporal databases/query languages has been studied from different perspectives, but the kind of temporal information they are able to store and retrieve is not always conveniently addressed. Here we assess a number of temporal query languages with respect to the modelling of time intervals, interval relationships and states, which can be thought of as the building blocks to represent and reason about a large and important class of historic information. To survey the facilities and issues which are particular to certain temporal query languages not only gives an idea about how useful they can be in particular contexts, but also gives an interesting insight in how these issues are, in many cases, ultimately inherent to the database paradigm. While in the area of AI declarative languages are usually the preferred choice, other areas of CS heavily rely on the extended relational paradigm. This paper, then, will be concerned with the representation of historic information in two well known temporal query languages: it Templog in the context of temporal deductive databases, and it TSQL2 in the context of temporal relational databases. We hope the results highlighted here will increase cross-fertilisation between different communities. This article can be related to recent publications drawing the attention towards the different approaches followed by the Databases and AI communities when using time-related concepts

A Survey on IT-Techniques for a Dynamic Emergency Management in Large Infrastructures

This deliverable is a survey on the IT techniques that are relevant to the three use cases of the project EMILI. It describes the state-of-the-art in four complementary IT areas: Data cleansing, supervisory control and data acquisition, wireless sensor networks and complex event processing. Even though the deliverable’s authors have tried to avoid a too technical language and have tried to explain every concept referred to, the deliverable might seem rather technical to readers so far little familiar with the techniques it describes

A Formal Framework for Complex Event Processing

Complex Event Processing (CEP) has emerged as the unifying field for technologies that require processing and correlating distributed data sources in real-time. CEP finds applications in diverse domains, which has resulted in a large number of proposals for expressing and processing complex events. However, existing CEP languages lack from a clear semantics, making them hard to understand and generalize. Moreover, there are no general techniques for evaluating CEP query languages with clear performance guarantees. In this paper we embark on the task of giving a rigorous and efficient framework to CEP. We propose a formal language for specifying complex events, called CEL, that contains the main features used in the literature and has a denotational and compositional semantics. We also formalize the so-called selection strategies, which had only been presented as by-design extensions to existing frameworks. With a well-defined semantics at hand, we discuss how to efficiently process complex events by evaluating CEL formulas with unary filters. We start by studying the syntactical properties of CEL and propose rewriting optimization techniques for simplifying the evaluation of formulas. Then, we introduce a formal computational model for CEP, called complex event automata (CEA), and study how to compile CEL formulas with unary filters into CEA. Furthermore, we provide efficient algorithms for evaluating CEA over event streams using constant time per event followed by constant-delay enumeration of the results. Finally, we gather the main results of this work to present an efficient and declarative framework for CEP

Using argumentation to solve conflicting situations in users' preferences in ambient assisted living

Preferences are fundamental in decision making, so understanding preference management is key in developing systems that guide the choices of the users. These choices can be decided through argument(s) which are known to have various strengths, as one argument can rely on more certain or vital information than the other. We explored argumentation technique from a previous study, and validated its potentials by applying to it several real life scenarios. The exploration demonstrates the usefulness of argumentation in handling conflicting preferences and inconsistencies, and provides effective ways to manage, reason and represents users' preferences. Using argumentation, we provide a practical implementation of a system to manage conflicting situations, and a simple interface that aids the flow of preferences from users to the system. We illustrated using the interface, how the changes in users' preferences can effect system output in a smart home. This article describes the functionalities of the implemented system, and illustrates the functions by solving some of the complexities in users' preferences in a real smart home. The system detects potential conflicts, and tries solve them using a redefined precedence order among some preference criteria. We also show how our system is capable of interacting with external sources data. The system was used to access and use live data of a UK supermarket chain store, through their application programming interface (API) and provide users suggestions on their eating habits, based on their set preference(s). The system was used to filter specific products from the live data, and check the product description, before advising the user accordingly

Contexts and context-awareness revisited from an intelligent environments perspective

Context is a useful concept somehow unconsciously used by humans in daily life problem-solving. Recently several subareas of computer science have been increasingly trying to rely on this concept to design systems with practical use in certain predefined circumstances. The perception is that imbuing in the system certain context-awareness qualities can support intelligent decision-making in specific practical situations. Despite a significant number of implemented systems which aim at providing context-awareness there is a lack of commonly accepted and used methodologies and tools. At the root of this, is the lack of agreement on a set of good principles or standards which can act as a guide to the scientific community and the developers interested in this class of systems. There have been some extensive surveys on the use of context, still there is no theoretical corpus emerging which we can use to discuss the essential concepts making up the fabric of contexts and its use by system developers. Here we attempted such enterprise at a level which is more formal than popular surveys, in a way that is not implementation dependent and in a way that highlights key concepts of relevance to developers. We reassessed first the basic concepts identifying the need to more prominently consider system beneficiaries’ satisfaction. We then transfer explicitly these values to a more formal outline of the basic components and the operations which emerge as relevant. We identify and highlight the tasks of context activation, comparison, influence, construction, and interaction. We hint at how these may work in practice and explained these through examples. We show how the theory is flexible enough by generalizing it to multiusers so that optimization of global preferences and expectations is used to drive system development and system behaviour

Generating Linear Orders of Events for Geospatial Domains

Events in the world do not occur in neat chronological order, but may take place, for example, during or overlapping each other, or as simultaneous events. Efficient summaries of real-world events are important in many disciplines and require events to be modeled in a linear fashion. This thesis focuses on modeling events as intervals and using relations between the events to derive linear orders from more complex partially ordered sets. A method is developed for mapping Allen\u27s thirteen temporal relations to only two relations, before and equals, which allow a linear ordering of all events present in the set. This mapping requires additional constraints to preserve semantics of the original relations as the orders are generated. Depending on the relations present, several linear orders may be possible, and methods are discussed of filtering the possible orders so as to present only the most plausible orders to a user. The result is a methodology that allows plausible linear orders to be automatically generated from partially-ordered sets of events

Detección y representación de eventos en un ambiente académico inteligente

112 páginas. Maestría en Ciencias de la ComputaciónUn Ambiente Inteligente es un espacio físico o virtual que es capaz de responder a las necesidades de los usuarios según el contexto. Un Evento es aquello que ocurre dentro de un ambiente, el cual se caracteriza por variables de tiempo (en qué momento sucede), espacio (en qué lugar) y persona (quién participa). En particular, en este trabajo se aborda la detección y representación de eventos que ocurren en un ambiente Académico inteligente; el tipo de eventos académicos que se consideran son: cursos, asesorías, seminarios, presentaciones, entre otros. En este documento de resultados se presenta un diseño ontológico para el modelado de contexto basado en eventos como núcleo del modelo, que es extensible y adaptable al dominio académico. El modelo ontológico es utilizado para la identificación de eventos académicos a partir de los datos adquiridos del entorno mediante el uso de reglas de decisión. Además, el modelo ontológico se usa para razonar con la información obtenida de los eventos identifícados. El modelo de ontologías basado en eventos considera cinco aspectos contextuales con una perspectiva modular: persona, temporalidad (tiempo), espacialidad (ubicación), red (recursos para adquirir datos del ambiente) y evento (eventos académicos). Para la evaluación del modelo de ontologías se llevó a cabo un proceso enfocado en: a) la extensibilidad y adaptación de escenarios de casos de uso en eventos académicos; b) el nivel de razonamiento mediante el uso de preguntas de competencia relacionadas con eventos académicos identifícados; c) la consistencia y la coherencia del modelo propuesto. La evaluación del proceso muestra resultados prometedores para el modelo antológico basado en eventos.Consejo Mexiquense de Ciencia y Tecnología (México)

Web-oriented Event Processing

How can the Web be made situation-aware? Event processing is a suitable technology for gaining the necessary real-time results. The Web, however, has many users and many application domains. Thus, we developed multi-schema friendly data models allowing the re-use and mix from diverse users and application domains. Furthermore, our methods describe protocols to exchange events on the Web, algorithms to execute the language and to calculate access rights