The rapid evolution of software paradigms, wireless technologies and mobile devices induced the emergence of new applications called context-aware services oriented applications. Such applications provide appropriate services or relevant information to the user or other applications to perform a specific task. An important challenge in such applications development process is context modeling and reasoning. Ontology based models presents the most promising instrument for context modeling and offers possibility of applying ontology reasoning techniques. the aim of context reasoning is converting low-level context to highlevel context in order to provide customized services to users. In this paper, we present an architecture for the development of context aware services based on ontologies. We also highlight our context metamodel and discuss about reasoning process for e-health systems.

The challenge in the development of complex systems is to cope with the dynamic nature of the user's profile, especially when such systems are exposed to the large public through the Internet. In Service oriented computing (SOC), a service may interact with several types of service clients. The central problem is, therefore, how to model the multidimensional aspect of service clients' needs and requirements. To tackle this problem, we propose in this paper the concept of the multiview service as a first class modeling entity that permits the representation of the needs and requirements of end-users by separating their concerns. Such adaptable services must carefully be analyzed and designed. However, current works on service oriented analysis and design (SOAD) largely focus on defining processes to develop business processes and services without considering user-aware variability. In the present paper we present an MDA framework for a muliview SOAD process for the development of highly adaptable services. We specify transformations as a collection of rules implemented in ATL. The proposal is illustrated by a simple example.

VUML is a view-based analysis/design method offering a formalism (UML profile) and a process to model software systems through objects and views. The main extension to UML is the multiview class whose goal is to store and deliver information according to the user's viewpoint. VUML supports the dynamic change of viewpoints and offers mechanisms to describe view dependencies. On the semantics side, the VUML meta-model extends the UML one with OCL rules. VUML proposes also a generic implementation pattern to generate the object code corresponding to a VUML class diagram. The proposed pattern uses delegation, handle technique and polymorphism to implement views. In this paper, we present a model driven implementation of this pattern, which integrates the multi-user aspect and supports Java language. We propose a code generation technique that respects the pattern and uses the MDA approach. We specify transformations as a collection of rules implemented in ATL. The proposal is illustrated by a simple example.

Model composition is considered as a crucial activity in model driven software development (MDSD). It is a common feature when adopting a multi-modeling approach to analyze and design software systems. Similar modular approaches are known under several names such as viewpoints, aspects, subjects, etc. In previous works, we proposed a view-based UML profile called VUML. In this paper, we describe a conceptual framework whose goal is to separate the generic composition part from the specific part dedicated to a given modeling domain. We apply our approach to the composition of UML class diagrams into one VUML class diagram.

We propose an extension of the Viterbi algorithm that makes second-order hidden Markov models computationally efficient. A comparative study between first-order (HMM1s) and second-order Markov models (HMM2s) is carried out. Experimental results show that HMM2s provide a better state occupancy modeling and, alone, have performances comparable with HMM1s plus postprocessing.

A recognizer for isolated words based on second order hidden Markov models (HMMs) is presented. This system is compared with the usual first order one. To evaluate the performances of both systems, a database of French digits is used. Results are more accurate with the recognizer using second-order hidden Markov process. A version of the Viterbi algorithm which is suited to continuous-speech recognition is described. This version, called Viterbi-block allows segmentation and labeling of an unknown utterance during its processing, whereas the classical Viterbi algorithm waits until the end of the sentence before backtracking the best path. This algorithm is based on a local optimum comparison of the different probabilities computed by the Viterbi algorithm during the time warping of a shift window of fixed length in the signal and the different HMMs. Different criteria of comparison between the probabilities of different paths are tried and assessed.>