The growing percentage of the elderly population within modern society is remarkable. Additionally, the aging process comes with specific individual needs, which require the provision of different custom-made (personalized) care services for each person. As these needs change throughout life, service providers have to adjust the services (service evolution) to reflect new (or obsoleted) necessities. To answer this need, an approach for the integration of services from various providers, leveraging on collaboration to supply better personalized and evolutionary care services for elderly, is proposed. As such, the development and application of and Elderly Care Ecosystem (ECE) framework is presented. An evaluation of this system to show the utility and applicability of the approach is based on a survey with domain experts. Results of the validation process are presented and analyzed.

Resilience measurement can be viewed as a multicriteria hierarchical decision making problem since calculating the final level of resilience involves measuring different criteria, at several hierarchical levels, and then merging the information together. In this paper, a resilience model for disaster rescue networks is discussed with a full-reinforcement operator, denoted continuous reinforcement operator. This approach is tested with different levels of reinforcement and the results are compared with those from a Fuzzy Inference System. The proposed approach offers interesting features to support balanced development of disaster rescue networks and facilitates managerial decisions by imposing standards for criteria to penalize or reward the information fusion process.

A conceptual architecture for an ambient assisted living ecosystem is introduced with the objective of facilitating the development and provision of integrated care and assistance services for senior citizens. These services are the result of collaboration among various stakeholders. An example of service design in this context is also presented.

Demographic changes worldwide are generating aged populations that bring sustainability challenges to the healthcare and social care systems. Therefore solutions that provide elderly citizens the chance to remain at their homes surrounded by an environment that takes care of them are needed. To support such environment the development of an ecosystem of products and services for Ambient Assisted Living is being carried out within the context of the AAL4ALL project. The provision of care and assistance services requires collaboration of multiple stakeholders which implies, under a socio-technical perspective, mechanisms for organization, governance and collaboration support among them. In this context, this paper presents an approach for modeling the management of such ecosystem using the i* modeling framework.

The notion of service-enhanced product offers new perspectives for value creation and differentiation in manufacturing. In the case of complex and highly customized products, the inclusion of business services that add value to the product typically require the collaboration of multiple stakeholders. In order to facilitate the co-creation and delivery of composite services, a proper collaborative environment is needed. This paper introduces a cloud-based collaborative environment, designed to support a mix of collaborative enterprise networks involved in the solar energy sector.

Both research and practice have shown that preexistence of long-term associations/clusters of active and competitive organizations, the so-called virtual organizations breeding environments (VBEs), can greatly enhance dynamic creation of virtual organizations (VOs). During the past decade, a number of VBEs are formed worldwide, mostly among organizations located in a common region that, in principle, have common business culture and other similarities, and primarily focus on static lines of activities. The second-generation VBEs addressed in this paper; however, aim to focus on associations/clusters that are not bound to geographical regions or static lines of activities, and wish to act as well recognized and competitive entities in the society/market, facilitating time/cost effective and fluid configuration, and establishment of dynamic VOs. The proposed VBEs apply supporting information and communication technology infrastructures, tools, and services that provide common grounds for the interaction and cooperation among their member organizations. Furthermore, these multiregional VBEs assist with the needed evolution of VOs, introducing new approaches and mechanisms to build trust, define the needed collaboration business culture, and establish the common value systems and working/sharing principles among their independent organizations, among others. The paper introduces a number of models, methodologies, and tools that are designed and developed supporting both the management as well as successful operation of the second-generation VBEs.

The establishment of a common value system is an important element for the sustainability of collaborative networks. This paper discusses the role of value systems in the VO breeding environment when the promotion of the cooperation is based on reciprocity mechanism. Some scenarios are included in the discussion and illustrations are given based on data from real networks.

Abstract Collaborative networked organizations are complex entities whose proper understanding, design, implementation, and management require the integration of different modeling perspectives. A comprehensive modeling framework is therefore proposed as a first step towards the elaboration of a reference model for collaborative networks. Modeling tools and theories developed in other disciplines are also analyzed in terms of their potential applicability in this domain. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The identification and characterization of collaboration benefits is an important element for the wide adoption of the collaborative networks paradigm. This paper introduces an approach for the analysis of benefits in collaborative processes for networks of enterprises. The potential application of some indicators derived from this analysis is also discussed in the VO breeding environment context. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The wide dissemination and effective materialization of the foreseen benefits of dynamic virtual organizations require a holistic approach to understand, model, and develop the needed infrastructures and tools to support the full life cycle of this organizational paradigm. Under this scope, the ECOLEAD integrated project was launched with the aim of creating the necessary foundations and mechanisms for establishing an advanced network-based industry society. The main underlying concepts, approach and preliminary results of this ongoing initiative are briefly summarized. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Effectiveness of the virtual organization (VO) creation process is the base for the possibility of having truly dynamic VOs in response to collaboration opportunities. A realistic approach to materialize agility in VO creation is the assumption of a VO Breeding Environment. In this context, a discussion of the process and suggested functionalities towards a VO creation framework are presented. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The design and development of invisible, easy to use and affordable ICT infrastructures is a key prerequisite for the effective large-scale implantation of the collaborative networks organizations such as virtual organizations, professional virtual communities, e-science communities, etc. This paper introduces an overview of the main classes of infrastructure required by different types of virtual organizations and the main approaches being followed in the European projects in the area.

The growing numbers of elderly population impose an urgent need to develop new approaches to care provision. The convergence of a number of technologies such as multi-agent systems, federated information management, safe communications, hypermedia interfaces, rich sensorial environments, increased intelligence of home appliances, and collaborative virtual environments, represents an important enabling factor for the design and development of virtual elderly support community environments. In this paper, a platform based on mobile agents combined with federated information management mechanisms is introduced as a flexible infrastructure on top of which specialized care services can be built.

This paper describes the concept of fitting autonomy for remote operation systems, which means that the autonomy of the remote place is defined in a case-by-case basis, taking into account the requirements of the applications and the characteristics of the communication channels. Thus, high levels of flexibility and independence on the characteristics of the communication channels are achieved. An architecture for mobile agents equipped with execution supervision is adopted as a solution to implement this approach. An application of these concepts in the context of the remote manipulation of a robot through the Internet is described.

To remain competitive in the aggressive global market, the tourism industry and service providers face the need to collaborate and share their expertise and resources, as well as their costs and risks. The paradigm of the virtual enterprise addresses the necessary horizontal infrastructure needed to support such a collaboration framework. Designing a Web-based Tourism Information System (WTIS) as a virtual enterprise requires the proper infrastructure that supports the enterprises' inter-operation, task sharing, and federated information management. This paper addresses the main requirements and research challenges, and describes a reference architecture for the WTIS, focusing on a novel horizontal infrastructure to support the Virtual Tourism Enterprises and provide the necessary basis for vertical value-added-services developed on top of the infrastructure.

This paper describes an ongoing work on the application of machine learning techniques in the domain of water distribution networks. This research is performed in the framework of the European project WATERNET, whose aim is to develop a system to control and manage water distribution networks. WATERNET is composed of a supervision system, a distributed information management subsystem, an optimization subsystem, a water quality monitoring subsystem, and a simulation subsystem. In addition to these components, a machine learning subsystem is included to extract knowledge from historical data and improve the performance of the water management system. This paper is focused on the approach and methodology followed for the development of the machine learning subsystem. The basic raw material for this work are historical data from a Portuguese water distribution company that has 45 water stations and some of them with six years of data collected every five minutes. The paper also shows the first results obtained, discusses difficulties found in the performed experiments and introduces an architecture based on qualitative models/causal relationships to ease the process of knowledge extraction from the historical data and the assessment of the extracted knowledge.

A framework for planning and supervision of robotized assembly tasks is initially presented, with emphasis on failure recovery. The approach to the integration services and the modeling of tasks, resources and environment is briefly described. A planning strategy and domain knowledge for nominal plan execution is presented. Through the use of machine learning techniques, the supervision architecture will be given capabilities for improving its performance over time. In particular, an approach for memorizing failure recovery episodes, based on abstraction, deductive generalization and feature construction, is presented. Recovery planning consists of adapting plan skeletons from similar episodes previously occurred.

A generic architecture for evolutive supervision of robotized assembly tasks, in a context of integrated manufacturing systems, is presented. This architecture provides, at different levels of abstraction, functions for dispatching actions, monitoring their execution, and diagnosing and recovering from failures. The problem of integration of legacy systems is discussed and an implementation approach described. Modeling execution failures through taxonomies and causal relations plays a central role in diagnosis and recovery. Through the use of machine learning techniques, the supervision architecture will be given capabilities for improving its performance over time. Particular attention is given to the inductive generation of structured classification knowledge for diagnosis. Methodologies used, performed experiments, and obtained results are described in detail.

A generic architecture for evolutive supervision of robotized assembly tasks is presented. This architecture provides, at different levels of abstraction, functions for dispatching actions, monitoring their execution, and diagnosing and recovering from failures. Modeling execution failures through taxonomies and causal networks plays a central role in diagnosis and recovery. Through the use of machine learning techniques, the supervision architecture will be given capabilities for improving its performance over time. Particular attention is given to the inductive generation of structured classification knowledge for diagnosis. The applied methodologies, performed experiments and obtained results are described in detail.

Research results concerning error detection and recovery in robotized assembly systems, key components of flexible manufacturing systems, are presented. A planning strategy and domain knowledge for nominal plan execution and for error recovery is described. A supervision architecture provides, at different levels of abstraction, functions for dispatching actions, monitoring their execution, and diagnosing and recovering from failures. Through the use of machine learning techniques, the supervision architecture will be given capabilities for improving its performance over time. Particular attention is given to the inductive generation of structured classification knowledge for diagnosis.

A generic architecture for execution supervision of robotic assembly tasks is presented. This architecture provides, at different levels of abstraction, functions for dispatching actions, monitoring their execution, and diagnosing and recovering from failures. Modeling execution failures through taxonomies and causal networks plays a central role in diagnosis and recovery. A discussion on the process of acquisition of such monitoring knowledge is made. Through the use of machine learning techniques, the supervision architecture will be given capabilities for improving its performance over time. Preliminary results of applying machine learning in this area are presented and planned extensions discussed.>