As society is aging it is imperative to find suitable technologies that can enable seniors to live in their own homes longer to minimize the social costs associated with institutional care. While there are many apps and gadgets to deal with individual situations such as fall detection, smart medicine dispenser, remote doctor visit etc. there are no comprehensive holistic solutions that can deal with most of the challenges associated with aging. This is a complex task involving many disciplines. At West Virginia University (USA), we put together an interdisciplinary group including Electrical Engineers, Computer Scientists, Computer Engineers, Medical and Healthcare Professionals and Social Workers to create a realistic testbed to demonstrate integrated solutions that can be scaled-up by start-up companies using a wide variety of resources available at the University. This system known as RANIA (Residents Aware Network for Intelligent Assistance) is being developed by a group of nearly 100 students under the guidance of faculty from the College of Engineering, School of Health Sciences and the School of Social Work. In addition, we have also created a Collaboratory to enable participation from institutions around the world to create their own unique solutions suitable for specific environments. We believe this project can have profound impact on aging populations around the world by establishing the technical feasibility and economic viability of technologies that can enhance quality of living not only by delaying the need for institutional care but also reducing social costs associated with caring for seniors.

With the ever-increasing amount of data and associated knowledge required to perform many modern-day tasks, quickly finding context-sensitive information can contribute to significant gains in knowledge worker productivity. Here, we describe the design and construction of a system, called a Personal Knowledge Advantage Machine (pKaM), to assist users while they perform knowledge based tasks. In this paper, we illustrate this idea by using the computer programming domain, which undoubtedly is a knowledge-intensive task, as an example. We first describe the architecture of a pKaM followed by a description of how it may be used by a programmer new to the Python language. The pKaM system may be viewed as a collection of agents that discover, mark-up, organize, display and present contextually relevant pieces of knowledge to the worker during the entire life-cycle of the task. The design of pKaM emphasizes the use of the plug-and-play approach so that it can be adapted to any domain by merely plugging-in a new domain knowledge base. As this idea gains currency, it is our hope that open-source knowledge bases organized along the lines described here will become available for many domains.

Knowledge advantage Machine (KaM) is an advanced system for knowledge exploitation. In this paper, we propose a Behavior Centric Service Discovery model, which helps one or more knowledge-workers to discover useful knowledge objects dubbed JANs, and then link the JANs into a personal knowledge and a group knowledge network. We construct JAN as a service to semantically present three categories of service behavior: expected service behavior that presents what requestor expects it to serve; actual service behavior that presents how it offers its service; and quality evaluation that presents whether its service behavior is consistent with requestor's expectation by checking conformance. On the basis of JAN linking, we build a KaM discovery Agent prototype to implement JAN discovery and linking. This is illustrated using an academic research scenario. Experimental results show that the proposed method is feasible and effective.

This is a milestone year for the IEEE International WETICE Conference. We are celebrating its 25th year - the Silver Jubilee, in Paris, France on June 13-15, 2016. WETICE started in 1992 as a collection of workshops with a common theme of Collaboration Technologies at West Virginia University's Concurrent Engineering Research Center (CERC), an industry-university partnership funded by the Defense Advanced Research Project Agency (DARPA) in Morgantown, West Virginia, USA. Its original full title was Workshops on Enabling Technologies: Infrastructures for Collaborative Enterprises with a "clever" acronym of WETICE. Initially it was held in West Virginia for the first four years, then migrated to other institutions in the US such as Stanford University (1996, 1998, 1999), Massachusetts Institute of Technology (MIT, 1997, 2001), National Institute of Standards and Technology (NIST, 2000), and finally to the Carnegie Mellon University (CMU) in 2002. It attracted many participants from various European countries practically from its beginning. In 2003 WETICE was held in Europe for the first time in Linz, Austria, and since then it continued to be held in Europe with the exception of Tunisia in 2013. The countries that hosted WETICE very cheerfully and successfully since 2003 are Austria, Sweden, UK, Italy (three times), France (four times), Greece, The Netherlands, Tunisia, and Cyprus. The comments below from the past and present leaders (in various capacities) of WETICE reflect their personal experiences and observations. Some have commented on how they got involved with the conference in the very early stages of their academic careers; others reflected on how the topics addressed by WETICE have evolved. These comments also show how WETICE focused on cutting edge topics and followed them through as they morphed.

Organizational studies and analyses of distributed engineering processes and other cooperative activities in the areas of training, expertise or distance education show business needs into solutions for organizing their activities around a workspace that can be shared or distributed and virtual. In this era of global competitiveness, the economic space reflects a constantly reorganizing movement, in which companies are globalized and internationalized 1. And this leads in both cases to an organization in teams, units or task forces increasingly geographically distributed. The procedures for design and engineering are being redefined to fit the new organization by anticipating solutions to avoid the disadvantages of this new organization, on one hand, and to benefit from its advantages on the other hand. This resulted in a need for research on a new organization of group activities, new generic software used in various fields of activities and new architectures for software specific to a particular area of activity. Different research areas are affected by this issue and are classified under the multidisciplinary theme of collaborative enterprises. Several research teams from the academic and industrial worlds have examined the emerging problems of the distribution of traditional engineering activities and the creation of new collaborative work procedures. Context-awareness in collaborative systems is being investigated for emergent technologies such as machine to machine (M2M) technologies 2. The multiplicity of requirements, both from the organizational and software point of views, for these studies makes them a sought after multidisciplinary field in which we can distinguish different disciplines, different applications and different views for each discipline and for each application. Autonomic computing, and cloud computing 3, service-oriented architecture and Web services for both real-time 4 and standard applications 5, as well as aspect-oriented programming 6 are becoming key technologies for designing and implementing collaborative systems. In an effort to disseminate the recent advances in this field and to stimulate discussion on the future research directions while enabling research interests toward the development and applications of collaborative systems, a special issue of Wiley Concurrency and Computation: Practice and Experience has been dedicated to recent developments in collaborative systems. This special issue presents a total of nine papers in the most active areas of research in collaborative systems. The paper by Nesrine Khabou et al. 7 titled ‘Threshold-based Context Analysis Approach For Ubiquitous Systems’ proposes an analysis approach for collaborative ubiquitous systems. The approach aims at analyzing context information and detecting significant abnormal changes using thresholds for tracking down context changes. The paper by Fatma Krichen et al. 8 titled ‘Development of Reconfigurable Distributed Embedded Systems with a Model-Driven Approach’ presents a methodology to design reconfigurable distributed real-time embedded systems with temporal and resources constraints. A model-driven engineering approach is adopted to handle the complexity of the design and implementation process. The paper by Mahdi Ben Alaya et al. 9 titled ‘FRAMESELF: An ontology-based framework for the self-management of M2M systems’ proposes a framework implementing the different steps of autonomic management for M2M networks. The approach uses representation based on ontologies and graphs to describe the M2M concepts and relationship. The paper by Mohamed Sellami et al. 10 titled ‘A Decentralized and Service-Based Solution for Data Mediation: The case for Data Providing Service Compositions’ deals with Web services and semantic mediation and addresses the problem of data heterogeneity in service composition. The authors propose a service-based approach for automatically inserting appropriate mediation services in Data-as-a-Service compositions to resolve structural heterogeneities in their data flow. The paper by Kevin Brown et al. 11 titled ‘Fine-grained filtering to provide access control for data providing services within collaborative environments’ deals with Web services for data retrieval and semantic annotation using ontology-based descriptions. The defined approach relies on a filtering ontology allowing to extend extensible access control markup language policies to reference filtering classes. The paper by Antonio Cuomo et al. 12 titled ‘Planting Parallel Program Simulation on the Cloud’ introduces a cloud-based concurrent simulation framework for efficient performance prediction of parallel programs. The accuracy and the validity are proven through a case study. The paper by Magdalena Punceva et al. 13 titled ‘Incentivising Resource Sharing in Social Clouds’ addresses cloud applications for social networking. An incentive approach is elaborated for resources sharing. The approach has a significant potential for improving resource utilization and making available additional capacity. The paper by Emiliano Tramontana et al. 14 titled ‘Providing QoS strategies and Cloud-integration to Web Servers by means of Aspects’ proposes an aspect-oriented approach for handling of QoS parameters. The approach is applied to improve the performances of Web servers. The paper by Nicola Capodieci et al. 15 titled ‘Context-awareness in the Deregulated Electric Energy Market: an Agent-based Approach’ proposes a context-aware agent-based approach for simulation. The case of energy market is studied for the future smart grids. Different context parameters are considered including weather forecasting. The guest editors of this special issue would like to thank all referees for providing thoughtful and knowledgeable reviews and for their substantial contributions to the final revised versions appearing in this special issue. They also would like to thank the Wiley Concurrency and Computation: Practice and Experience editor in chief, Professor Dr. Geoffrey Fox, for his valuable suggestions and all the authors who have submitted to this special issue.

Journal Article Enabling Technologies: Infrastructure for Collaborative Enterprises Get access Slim Kallel, Slim Kallel * 1ReDCAD Laboratory, University of Sfax, B.P. 1173, 3038 Sfax, Tunisia *Corresponding author: slim.kallel@fsegs.rnu.tn Search for other works by this author on: Oxford Academic Google Scholar Mohamed Jmaiel, Mohamed Jmaiel 1ReDCAD Laboratory, University of Sfax, B.P. 1173, 3038 Sfax, Tunisia2Research Center for Computer Science, Multimedia and Digital Data Processing of Sfax, B.P. 275, Sakiet Ezzit, 3021 Sfax, Tunisia Search for other works by this author on: Oxford Academic Google Scholar Sumitra Reddy Sumitra Reddy 3Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV, USA Search for other works by this author on: Oxford Academic Google Scholar The Computer Journal, Volume 58, Issue 3, March 2015, Page 355, https://doi.org/10.1093/comjnl/bxu155 Published: 05 January 2015 Article history Received: 30 November 2014 Revision received: 03 December 2014 Published: 05 January 2015

In this paper we describe the Discovery Agent of Vijjana, an umbrella project for creating a person-specific knowledge repository based on classification and analysis. Vijjana provides a framework designed for building collaborative knowledge networks that are domain specific and well bounded in search categories. Using the Vijjana model, we can envision creating an intelligent agent that presents context based information that is drawn from a personalized knowledge base. We call such an agent a Knowledge Advantage Machine (KaM) as it enables a user to take advantage of the personalized knowledge base to perform the task at hand more effectively - in much the same way mechanical advantage had been helping industrial workers. In this paper we discuss only the first part, namely the discovery agent. In this part the focus is on a conceptual way to bridge the gap between the presentation layer and the data access layer which is discussed here using the Object Relational Mapping through the Hibernate framework.

A workflow pattern could be defined as the methods by which a user typically utilizes a particular system. This paper presents a framework by which data mining techniques could be used to extract patterns from an individual's work flow data to exploit a type of architecture known as a Knowledge Advantage Machine (KAM). KAM is a type of semantic desktop and semantic web application that would assist people in constructing their own personal knowledge networks, as well as sharing that information in an efficient manner with colleagues using the same system. A KAM would be capable of automatically discovering new knowledge that is relevant to the user's personal ontology. Through experimentation, it is empirically demonstrated that a user's file usage patterns can be utilized by a software to automatically and seamlessly learn what is "important" as defined by the user. Further research is necessary to apply this principle to a more realizable KAM so that decisions can be fueled by work patterns as well as semantic or contextual information.

Collaboration is an important aspect in almost all fields of human life, and today the need for supporting collaboration is increased by the fact that we are always connected by means of different kinds of devices. In particular in the enterprise world, this need has emerged and satisfying it can lead to relevant benefits for companies. In the last years, enabling technologies have evolved to meet new and challenging requirements. The aim of this special issue is to provide a selection of the state of the art, emerging trends, new technologies and best practices in the field of technologies that enable collaboration. The idea was born at the 2014 IEEE WETICE Conference on "Enabling Technology: Infrastructure for Collaborative Enterprises", but the call was open to any submission. This special issue features three articles that concern technologies that enable collaboration. The first one, "Engineering And Implementing Software Architectural Patterns Based On Feedback Loops" by Dhaminda B. Abeywickrama, Nicklas Hoch and Franco Zambonelli, focuses on collaboration in decentralized system of autonomous service components. The paper proposes an Eclipse plug-in called SimSOTA, which supports the design and the implementation of self-adaptive systems. Different phases of the development are covered in a model-driven fashion based on self-adaptive architectural patterns. The second one, "Simulation Data Sharing to Foster Teamwork Collaboration" by Claudio Gargiulo, Delfina Malandrino, Donato Pirozzi and Vittorio Scarano, addresses the collaboration among engineers involved in Computational Fluid Dynamics (CFD) simulations. A Web-based system is presented, called Floasys, which was developed starting from the experience in a big automotive company. The third paper, "Investigation On The Optimal Properties Of Semi Active Control Devices With Continuous Control For Equipment Isolation" by Michela Basili and Maurizio De Angelis, faces the collaboration among devices, composing a single equipment. A control algorithm, derived from the Lyapunov method and adapted to the addressed problem is presented, which is able to achieve the optimal isolation properties of semi active variable stiffness devices with continuous control across the whole frequency spectrum. It is interesting to remark that all the accepted papers present a strong connection with real requirements, but meet them by solid models or theory. We also hope that these papers can solicit new research directions in the field. We would like to thank the editorial board of SCPE for the chance of arranging this special issue, and all the reviewers for their hard work.

Purpose - Our main purpose is to build an on-demand service discovery model to find useful knowledge object dubbed JAN whose service behaviour is consistent with the requestor's expectation. It goes beyond the keyword approach by incorporating behaviour centricity into the discovery process.Design/methodology/approach - We propose an approach of Behaviour Centric Service Discovery (BCSD), which is a new way to discover and construct useful JANs for building Knowledge advantage Machine (KaM). We bring the idea of JAN as a service to provide an abstract layer above web resources to achieve the uniqueness for different users sharing the same resources.Originality/value - This methodology puts in evidence about the definition of service behaviour, the conceptual modelling of BCSD, and the architecture model of KaM discovery Agent. Combined with ontology, semantic web service and multi-Agent techniques, we built a semantic service discovery model. We also proposed a method for quality evaluation with conformance checking of service behaviour, which we consider is an innovative and relevant contribution to the state of the art. The proposed BCSD model promotes an effective mechanism for knowledge management and sharing. The KaM discovery Agent is a very useful tool as it provides a model for dynamically creating self-describing knowledge objects for knowledge acquisition, management and sharing.Practical implications - The outcomes of the application is a prototype of the discovery Agent for one type of KaM user such as an academic. We present a JAN discovery implementation that involves user interaction at some points in an end-to-end process of finding relevant research papers. We developed a prototype of KaM discovery Agent based on the JADE project and integrated into OWL-S.

W ith the rapid development of the World Wide Web, huge amount of data has been growing exponentially in our daily life. Users will spend much more time on searching the information they really need than before. Even when they make the exactly same searching input, different users would have various goals. Otherwise, users commonly annotate the information resources or make search query according to their own behaviors. As a matter of fact, this process will bring fuzzy results and be time-consuming. Based on the above problems, we propose our methodology that to combine user’s context, users’ profile with users’ Folksonomies together to optimize personal search. At the end of this paper, we make an experiment to evaluate our methodology and from which we can conclude that our work performs better than other sample s.

A model named KaM_CRK is proposed, which can supply the clustered and ranked knowledge to the users on different contexts. By comparing the attributes of contexts and JANs, our findings indicate that our model can accumulate the JANs, whose attributes are similar with the user's contexts, together. By applying the KaM_CLU algorithm and Centre rank strategy into the KaM_CRK model, the model boosts a significant promotion on the accuracy of provision of user's knowledge. By analyzing the users' behaviors, the dynamic coefficient Behavior F is first presented in KaM_CLU. Compared to traditional approaches of K means and DBSCAN, the KaM_CLU algorithm does not need to initialize the number of clusters. Additionally, its synthetic results are more accurate, reasonable, and fit than other approaches for users. It is known from our evaluation through real data that our strategy performs better on time efficiency and user's satisfaction, which will save by 30% and promote by 5%, respectively.

A cyber-physical system is treated with a collaborative self-organizing knowledge network model, called Vijjana. While traditional communication between users of Vijjana forms a loosely coupled system, in cyber-physical system it is tightly-bound forming a policy-driven knowledge grid. If there is a compromised security in a cyber-physical system, the knowledge grid bootstraps to a subset grid, isolated from other nodes. A model for this bootstrap is proposed, which looks for carefully administered security policies in the cyber-physical system.

We present a new framework for visualization and retrieval of knowledge organized as a personal semantic web. This framework is an extension of other semantic web technologies and aims to achieve a fast, elegant solution to carrying your knowledge with you. The architecture described has been developed on the Google Android platform and embedded OpenGL. We call this a Personal Knowledge Advantage Machine (pKaM) as it is designed to access a personalized semantic network using a user-specific ontology. This also includes a graphical browser which enables a user visualize the portion of the semantic network that is relevant to the specific user context.

User centric interaction is an essential requirement in many types of web related applications. Always a basic expectation from the user is that the web interaction must be self-organizing and evolving in an organized pattern as the user interest progresses. This paper addresses such an expectation with an ontology pattern based Knowledge Advantage Machine [KAM]. It illustrates how this KAM system leads to the determination of a reliable context as the knowledge discovery is taking place.

This research reports agent activities in a collaborative, self-organizing, domain centric knowledge network, called Vijjana. Vijjana means classified knowledge in Sanskrit language. This model has been designed and implemented to assist users engaged in web activities, limiting the data retrieval to desired material only. The model Vijjana sits on the top layer of the cloud computing architecture, and with its agent activities develops a body of intelligent reasoning system which can semantically connect different dispersed users with their own knowledge nets. Vijjana model makes the cloud computing intelligibly usable for connecting different people working with the same domain specific interest. This provides a high order of accountability with assurance on confidentiality, integrity and availability.

Presents the introductory welcome message from the conference proceedings.