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Empowered smart objects have become a part of people everyday activities due to the evolution of pervasive computing technologies. In such scenario context awareness plays a fundamental role in enabling adaptation and contextual services. Up to now a lot of efforts have been done in representing context information such as location, time and users identity. At the same time not much attention has...
Smart objects are gradually integrating into people's everyday life. While many context-aware solutions for pervasive computing environments do not consider users social aspects, we believe smart objects should be social-aware. So Smart aims at filling the gap in social understanding of the user environment, presenting an ontology based context model to support social context representation and automated...
Context awareness service is one of the key features in ubiquitous computing system. In heterogeneous pervasive computing system, effective context modeling and reasoning are important to enable the collaboration and distributed reasoning among the agents. The effectiveness of the previous approaches for distributed reasoning significantly degrades when a large number of agents are involved. In order...
We present a new method to learn the model based on object parts extraction and grammar which can be applied to classification and recognition. Our approach is invariant to the scale and rotation of the objects. We use Structural Context feature to detect object parts. It is done comparing SC histograms of the model and image. We extract oriented triplets from centers of detected parts. We define...
The OWL 1has been as a modeling language to formalize context-awareness pervasive environments. And also, various kinds of context ontologies in the OWL are proposed to conceptualize the entities for describing pervasive computing environments. With increasingly considering about spatial and temporal expressive capabilities and properties related for pervasive computing, these approaches provide some...
Agent reasoning in large scale multi-agent systems requires techniques which often work with uncertainty and probability. In our research, we use trust and reputation principles to support agent reasoning and decisioning. Information about agents past behaviour and their qualities are transformed to multi-context trust. It allows to view a single agent from different point of views, because agents...
Information foraging and sensemaking with heterogeneous information are context-dependent activities. Thus visual analytics tools to support these activities must incorporate context. But, context is a difficult concept to define, model, and represent. Creating and representing context in support of visually-enabled reasoning about complex problems with complex information is a complementary but different...
In pervasive computing environment the contexts are usually imprecise and incomplete due to unreliable connectivity, user mobility, and resource constraints. In this paper we present an approach based on the Dempster-Shafer Theory (DST) for the reasoning with imprecise context. To solve the two fundamental issues of the DST, computation intensiveness and the Zadeh paradox, we filer out excrescent...
This paper proposes the sequential context inference (SCI) algorithm for Markov random field (MRF) image analysis. This algorithm is designed primarily for fast inference on an MRF model, but its application requires also a specific modeling architecture. The architecture is composed of a sequence of stages, each modeling the conditional probability of the labels, conditioned on a neighborhood of...
In order for the intelligent assistant systems to provide users with timely and appropriate assistances, most of them focus on what is considered to be the "rational" aspect of the user behaviors. However, since human desire is the fundamental driving force of human behaviors, without including users' desires, the system cannot provide most appropriate responses. We propose a hierarchical...
Toponym Disambiguation (TD) in Geographic Information Retrieval (GIR) systems is a crucial technique, which makes a direct impact on the quality of subsequent assignment of geographic focus to a document and that of establishment of spatial index as well as the effectiveness of the entire retrieval model as a whole. We explore the mechanism for human beings' dealing with the problem of TD. Human's...
Traditional security mechanisms can not satisfy the pervasive computing environment commendably. A dynamic trust model is proposed, utilizing the Dempster-Shafer (D-S) theory to model the diminution of the hypothesis set on trust evaluation with the accumulation of evidence. The trust expression of relationship between entities, the general formula of direct trust, indirect trust and integrated trust...
Grammar Induction (or Grammar Inference or Language Learning) is the process of learning of a grammar from training data of the positive and negative strings of the language. Genetic algorithms are amongst the techniques which provide successful result for the grammar induction. The paper describes a Pushdown Automata (PDA) simulator used to parse the training data with the grammar induced by the...
Varied context reasoning approaches are used across a variety of applications in the pervasive computing domain including: health monitoring, intrusion detection, airport security and military target tracking. The same types of context are being inferred in diverse ways across a number of platforms. For example, human activity has been inferred using a number of statistical, ontological, and logical...
Context is a key factor for providing intelligent service in ubiquitous computing environment. The usefulness of context is based on its correctness. As the context plays a crucial role in service performance, it is necessary to guarantee the reliability of context. But, it is almost impossible to scan the full aspects of the environment for the limited computing capability and unlimited modality...
Formal specifications and reasoning techniques in software modelling are needed to ensure the correctness of the system at the design phase. Event-B is a formal method with support tools that allows the stepwise development of reactive systems. Such systems include multi-agent systems as a subclass. In this paper, we propose an approach to specify capabilities of a number of software agents. We then...
Context-awareness service is one of the key features of ubiquitous paradigm. To intelligently and sensitively deal with the dynamic environment, a methodology effectively enabling the agent-based distributed reasoning needs to be developed. The existing modeling approaches focus on scenario-based acquisition, management, and representation of context. However, they are difficult to be adapted to agent-based...
The category theory based model (8th GrC Model) has been proposed as the ldquofinalrdquo GrC Model. This paper is to discuss its specialization into the category of qualitative fuzzy sets. Here are the main points: 1) Let Col be the collection of real world fuzzy sets on U, where U is a crisp set. 2) Let V be the type I fuzzy sets of col. Namely, V, denoted by MF(U), is the set of all membership functions...
We propose an ontology-based approach for inferences linking trust information in two different situations. That reasoning process can augment the typically sparse trust information, by inferring the missing information from other situational conditions, and can better support situation-aware trust management. Our work is more comprehensive in comparison with other models and considers various aspects...
We introduce F-ALCI, a federated version of the description logic ALCI. An F-ALCI ontology, like its package-based counterpart ALCIP-, consists of multiple ALCI ontologies that can import concepts or roles defined in other modules. Unlike ALCIP- which supports only contextualized negation, F-ALCI, supports contextualization of each of the logical connectives, a feature that allows more flexible reuse...
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