Designing wrapper components for e-services in integrating heterogeneous systems

Component-based approaches are becoming more and more popular to support Internet-based application development. Different component modeling approaches, however, can be adopted, obtaining different abstraction levels (either conceptual or operational). In this paper we present a component-based architecture for the design of e-applications, and discuss the concept of wrapper components as building blocks for the development of e-services, where these services are based on legacy systems. We discuss their characteristics and their applicability in Internet-based application development. Received: 30 October 2000 / Accepted: 9 January 2001 Published online: 28 June 2001     

On the observational theory of the CPS-calculus

We apply powerful proof-techniques of concurrency theory to study the observational theory of Thielecke’s CPS-calculus, a distillation of the target language of Continuation-Passing Style transforms. We define a labelled transition system from which we derive a (weak) labelled bisimilarity that completely characterises Morris’ context-equivalence. We prove a context lemma showing that Morris’ context-equivalence coincides with a simpler context-equivalence closed under a smaller class of contexts. Then we profit of the determinism of the CPS-calculus to give a simpler labelled characterisation of Morris’ equivalence, in the style of Abramsky’s applicative bisimilarity. We enhance our bisimulation proof-methods with up to bisimilarity and up to context proof techniques. We use our bisimulation proof techniques to investigate a few algebraic properties on diverging terms that cannot be proved using the original axiomatic semantics of the CPS-calculus.     

Segmentation of news videos based on audio-video information

In this paper, we propose an innovative architecture to segment a news video into the so-called “stories” by both using the included video and audio information. Segmentation of news into stories is one of the key issues for achieving efficient treatment of news-based digital libraries. While the relevance of this research problem is widely recognized in the scientific community, we are in presence of a few established solutions in the field. In our approach, the segmentation is performed in two steps: first, shots are classified by combining three different anchor shot detection algorithms using video information only. Then, the shot classification is improved by using a novel anchor shot detection method based on features extracted from the audio track. Tests on a large database confirm that the proposed system outperforms each single video-based method as well as their combination.

Improving Communication in E-democracy Using Natural Language Processing

E-democracy, the design and development of new techniques for improving communication between public administration and citizens, is a major application field for natural language processing and language engineering. Helping citizens access information in a friendly, intuitive way is the primary objective of a global e-democracy framework. The E-democracy European Network project (EDEN) aimed at discovering whether a particular NLP (natural language processing) approach could further e-democracy by increasing citizens' participation in the decision-making process. The goal was twofold: to test whether e-democracy requirements could be meet using advanced linguistic technology and to test whether augmented phrase structure grammars (APSGs) were robust and well-assessed enough to use in a real-world environment. Also, the aim is to develop two toolsets to improve communication between PAs and citizens in the context of urban planning: a set of NLP-based tools to simplify access to information and knowledge and a set of forum and polling devices     

A hybrid particle swarm optimization approach for the sequential ordering problem

The sequential ordering problem is a version of the asymmetric travelling salesman problem where precedence constraints on vertices are imposed. A tour is feasible if these constraints are fulfilled, and the objective is to find a feasible solution with minimum cost.     

A multi-objective evolutionary approach to image quality/compression trade-off in JPEG baseline algorithm

The JPEG algorithm is one of the most used tools for compressing images. The main factor affecting the performance of the JPEG compression is the quantization process, which exploits the values contained in two tables, called quantization tables. The compression ratio and the quality of the decoded images are determined by these values. Thus, the correct choice of the quantization tables is crucial to the performance of the JPEG algorithm. In this paper, a two-objective evolutionary algorithm is applied to generate a family of optimal quantization tables which produce different trade-offs between image compression and quality. Compression is measured in terms of difference in percentage between the sizes of the original and compressed images, whereas quality is computed as mean squared error between the reconstructed and the original images. We discuss the application of the proposed approach to well-known benchmark images and show how the quantization tables determined by our method improve the performance of the JPEG algorithm with respect to the default tables suggested in Annex K of the JPEG standard.     

Enabling energy-efficient and lossy-aware data compression in wireless sensor networks by multi-objective evolutionary optimization

Nodes of wireless sensor networks (WSNs) are typically powered by batteries with a limited capacity. Thus, energy is a primary constraint in the design and deployment of WSNs. Since radio communication is in general the main cause of power consumption, the different techniques proposed in the literature to improve energy efficiency have mainly focused on limiting transmission/reception of data, for instance, by adopting data compression and/or aggregation. The limited resources available in a sensor node demand, however, the development of specifically designed algorithms. To this aim, we propose an approach to perform lossy compression on single node based on a differential pulse code modulation scheme with quantization of the differences between consecutive samples. Since different combinations of the quantization process parameters determine different trade-offs between compression performance and information loss, we exploit a multi-objective evolutionary algorithm to generate a set of combinations of these parameters corresponding to different optimal trade-offs. The user can therefore choose the combination with the most suitable trade-off for the specific application. We tested our lossy compression approach on three datasets collected by real WSNs. We show that our approach can achieve significant compression ratios despite negligible reconstruction errors. Further, we discuss how our approach outperforms LTC, a lossy compression algorithm purposely designed to be embedded in sensor nodes, in terms of compression rate and complexity.     

Multimodal support to group dynamics

The complexity of group dynamics occurring in small group interactions often hinders the performance of teams. The availability of rich multimodal information about what is going on during the meeting makes it possible to explore the possibility of providing support to dysfunctional teams from facilitation to training sessions addressing both the individuals and the group as a whole. A necessary step in this direction is that of capturing and understanding group dynamics. In this paper, we discuss a particular scenario, in which meeting participants receive multimedia feedback on their relational behaviour, as a first step towards increasing self-awareness. We describe the background and the motivation for a coding scheme for annotating meeting recordings partially inspired by the Bales’ Interaction Process Analysis. This coding scheme was aimed at identifying suitable observable behavioural sequences. The study is complemented with an experimental investigation on the acceptability of such a service.

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A multimodal semantic location service for intelligent environments: an application for Smart Hospitals

This paper presents semantic models, mechanisms and a service to locate mobile entities in Smart and Intelligent Environments. The key feature of the service is the semantic integration of different positioning systems that not only enables the environment to handle transparently such physical positioning systems, but also to reason on location information coming from different systems and to combine it to obtain higher context information. Indeed, the service relies on the use of ontologies and rules to define a uniform, unambiguous and well-defined model for the location information, independently of the particular positioning system. Moreover, the location service performs logic and reasoning mechanisms to provide both physical and semantic locations of mobile objects and to infer the finest granularity in the case when a mobile object is located by more than one positioning system. Finally, we present an application of the proposed approach to the case of a Smart Hospital.