This paper puts forward a verification method for compound purposes and compound reasons to be used during purpose limitation.

When it is absolutely necessary to collect privacy related information, it is essential that privacy enhancing technologies (PETs) protect access to data - in general accomplished by using the concept of purposes bound to data. Compound purposes and reasons are an enhancement of purposes used during purpose limitation and binding and are more expressive than purposes in their general form. Data users specify their access needs by making use of compound reasons which are defined in terms of (compound) purposes. Purposes are organised in a lattice with purposes near the greatest lower bound (GLB) considered weak (less specific) and purposes near the least upper bound (LUB) considered strong (most specific).

Access is granted based on the verification of the statement of intent (from the data user) against the compound purpose bound to the data; however, because purposes are in a lattice, the data user is not limited to a statement of intent that matches the purposes bound to the data exactly - the statement can be a true reflection of their intent with the data. Hence, the verification of compound reasons against compound purposes cannot be accomplished by current published verification algorithms.

Before presenting the verification method, compound purposes and reasons, as well as the structures used to represent them, and the operators that are used to define compounds is presented. Finally, some thoughts on implementation are provided.

Responsive open learning environments (ROLEs) are the next generation of personal learning environments (PLEs). While PLEs rely on the simple aggregation of existing content and services mainly using Web 2.0 technologies, ROLEs are transforming lifelong learning by introducing a new infrastructure on a global scale while dealing with existing learning management systems, institutions, and technologies. The requirements engineering process in highly populated test-beds is as important as the technology development. In this paper, we will describe first experiences deploying ROLEs at two higher learning institutions in very different cultural settings. The Shanghai Jiao Tong University in China and at the “Center for Learning and Knowledge Management and Department of Information Management in Mechanical Engineering” (ZLW/IMA) at RWTH Aachen University have exposed ROLEs to theirs students in already established courses. The results demonstrated to readiness of the technology for large-scale trials and the benefits for the students leading to new insights in the design of ROLEs also for more informal learning situations.

Knowledge, innovations and their implementation in effective practices are essential for development in all fields of societal action, e.g. policy, business, health, education, and everyday life. However, managing the interrelations between knowledge, innovation and practice is complicated. Facilitation by suitable knowledge services is needed. This paper explores the theory of converging knowledge, innovation, and practice, discusses some advances in information systems development, and identifies general requirements for pragmatic knowledge services. A trialogical approach to knowledge creation and learning is adopted as a viable theoretical basis. Also three examples of novel knowledge services Opasnet, Innovillage, and Knowledge Practices Environment (KPE), are presented. Eventually, it is concluded that pragmatic knowledge services, as hybrid systems of information technology and its users, are not only means for creation of practical knowledge, but vehicles of a cultural change from individualistic perceptions of knowledge work towards mediated collaboration.

This paper offers an overview of the emerging domain of mobile governance as an offspring of the broader landscape of e-governance. Mobile governance initiatives have been deployed everywhere in parallel to the development of crowdsourced, open source software applications that facilitate the collection, aggregation, and dissemination of both information and data coming from different sources: citizens, organizations, public bodies, etc. Ultimately, mobile governance can be seen as a tool to promote the rule of law from a decentralized, distributed, and bottom-up perspective.

Siemens is well known for ambitious efforts in knowledge management, providing a series of innovative tools and applications within the intranet. References@BT is such a web-based application with currently more than 7,300 registered users from more than 70 countries. Its goal is to support the sharing of knowledge, experiences and best-practices globally within the Building Technologies division. Launched in 2005, References@BT features structured knowledge references, discussion forums, and a basic social networking service. In response to use demand, a new microblogging service, tightly integrated into References@BT, was implemented in March 2009. More than 500 authors have created around 2,600 microblog postings since then. Following a brief introduction into the community platform References@BT, we comprehensively describe the motivation, experiences and advantages for an organization in providing internal microblogging services. We provide detailed microblog usage statistics, analyzing the top ten users regarding postings and followers as well as the top ten topics. In doing so, we aim to shed light on microblogging usage and adoption within a globally distributed organization.

The paper explores the application of Web 2.0 technologies to support product development efforts in a global, virtual and cross-functional setting. It analyses the dichotomy between the prevailing hierarchical structure of CAD/PLM/PDM systems and the principles of the Social Web under the light of the emerging product development trends. Further it introduces the concept of Engineering 2.0, intended as a more bottom up and lightweight knowledge sharing approach to support early stage design decisions within virtual and cross-functional product development teams. The lessons learned collected from a cross-company study highlight how to further developblogs, wikis, forums and tags for the benefit of new product development teams, highlighting opportunities, challenges and no-go areas.

In this paper we present an approach to improving navigability of a hierarchically structured Web content. The approach is based on an integration of a tagging module and adoption of tag clouds as a navigational aid for such content. The main idea of this approach is to apply tagging for the purpose of a better highlighting of cross-references between information items across the hierarchy. Although in principle tag clouds have the potential to support efficient navigation in tagging systems, recent research identified a number of limitations. In particular, applying tag clouds within pragmatic limits of a typical user interface leads to poor navigational performance as tag clouds are vulnerable to a so-called pagination effect. In this paper, a solution to the pagination problem is discussed, implemented as a part of an Austrian online encyclopedia called Austria-Forum, and analyzed. In addition, a simulation-based evaluation of the new algorithm has been conducted. The first evaluation results are quite promising, as the efficient navigational properties are restored.

Collaborative Filtering(CF) is a well-known technique in recommender systems. CF exploits relationships between users and recommends items to the active user according to the ratings of his/her neighbors. CF suffers from the data sparsity problem, where users only rate a small set of items. That makes the computation of similarity between users imprecise and consequently reduces the accuracy of CF algorithms. In this article, we propose a clustering approach based on the social information of users to derive the recommendations. We study the application of this approach in two application scenarios: academic venue recommendation based on collaboration information and trust-based recommendation. Using the data from DBLP digital library and Epinion, the evaluation shows that our clustering technique based CF performs better than traditional CF algorithms.

Interactive video is increasingly becoming a more and more dominant feature of our media platforms. Especially due to the popular YouTube annotations framework, integrating graphical annotations in a video has become very fashionable these days. However, the current options are limited to a few graphical shapes for which the user can define as good as no dynamic behaviour. Despite the enormous demand for easy-creatable, interactive video there are no such advanced tools available.

In this article we describe an innovative approach, to realize dynamics and interactivity of video annotations. First we explain basic concepts of video-markup like the generic element model and visual descriptors. After that we introduce the event-tree model, which can be used to define event-handling in an interactive video formally as well as visually. By combining these basic concepts, we can give an effective tool to the video community for realizing interactive and dynamic video in a simple, intuitive and focused way.

One of the challenges in Dynamic Software Product Line (DSPL) is how to support the coordination of multiple instances of a service feature. In particular, there is a need for a decentralized decision-making capability that will be able to seamlessly integrate new instances of a service feature without an omniscient central controller. Because of the need for decentralization, we are investigating principles from self-organization in biological organisms. As an initial proof of concept, we have applied three bio-inspired techniques to a simple smart home scenario: quorum sensing based service activation, a firefly algorithm for synchronization, and a gossiping (epidemic) protocol for information dissemination. In this paper, we first explain why we selected those techniques using a set of motivating scenarios of a smart home and then describe our experiences in adopting them.

Web Services have become a standard for integration of systems in distributed environments. By using a set of open interoperability standards, they allow computer-computer interaction, regardless the programming languages and operating systems used. The Semantic Web Services, by its turn, make use of ontologies to describe their functionality in a more structural manner, allowing computers to reason about the information required and provided by them. Such a description also allows dynamic composition of several Web Services, when only one is not able to provide the desired functionality. There are scenarios, however, in which only the functional correctness is not enough to fulfill the user requirements, and a minimum level of quality should be guaranteed by their providers. In this context, this work presents an approach for dynamic Web Service composition that takes into account the composition overall quality. The proposed approach relies on a heuristics to efficiently perform the composition. In order to show the feasibility of the proposed approach, a Web Service composition application prototype was developed and experimented with public test sets, along with another approach that does not consider quality in the composition process. The results have shown that the proposed approach in general finds compositions with more quality, within a reasonable processing time.

Software components are used in various application domains, and many component models and frameworks have been proposed to fulfill domain-specific requirements. The general trend followed by these approaches is to provide ad-hoc models and tools for capturing these requirements and for implementing their support within dedicated runtime platforms, limited to features of the targeted domain. The challenge is then to propose more flexible solutions, where components reuse is domain agnostic. In this article, we present a framework supporting compositional construction and development of applications that must meet various extra-functional/domain-specific requirements. The key points of our contribution are: i) We target development of component-oriented applications where extra-functional requirements are expressed as annotations on the units of composition in the application architecture. ii) These annotations are implemented as open and extensible component-based containers, achieving full separation of functional and extra-functional concerns. iii) Finally, the full machinery is implemented using the Aspect-Oriented Programming paradigm. We validate our approach with two case studies: the first is related to real-time and embedded applications, while the

Visualization of search results is an essential step in the textual Information Retrieval (IR) process. Indeed, Information Retrieval Interfaces (IRIs) are used as a link between users and IR systems, a simple example being the ranked list proposed by common search engines. Due to the importance that takes visualization of search results, many interfaces have been proposed in the last decade (which can be textual, 2D or 3D IRIs). Two kinds of evaluation methods have been developed: (1) various evaluation methods of these interfaces were proposed aiming at validating ergonomic and cognitive aspects; (2) various evaluation methods were applied on information retrieval systems (IRS) aiming at measuring their effectiveness. However, as far as we know, these two kinds of evaluation methods are disjoint. Indeed, considering a given IRI associated to a given IRS, what happens if we associate this IRI to another IRS not having the same effectiveness. In this context, we propose an IRI evaluation framework aimed at evaluating the suitability of any IRI to different IR scenarios. First of all, we define the notion of IR scenario as a combination of features related to users, IR tasks and IR systems. We have implemented the framework through a specific evaluation platform that enables performing IRI evaluations and that helps end-users (e.g. IRS developers or IRI designers) in choosing the most suitable IRI for a specific IR scenario.

Recently, IEEE 802.16 Worldwide Interoperability for Microwave Access (WiMAX for short) has provided us with low-cost, high efficiency and high bandwidth network services. However, as with the WiFi, the radio wave transmission also makes the WiMAX face the wireless transmission security problem. To solve this problem, the IEEE802.16Std during its development stage defines the Privacy Key Management (PKM for short) authentication process which offers a one-way authentication. However, using a one-way authentication, an SS may connect to a fake BS. Mutual authentication, like that developed for PKMv2, can avoid this problem. Therefore, in this paper, we propose an authentication key management approach, called Diffie-Hellman-PKDS-based authentication method (DiHam for short), which employs a secret door asymmetric one-way function, Public Key Distribution System (PKDS for short), to improve current security level of facility authentication between WiMAX's BS and SS. We further integrate the PKMv1 and the DiHam into a system, called PKM-DiHam (P-DiHam for short), in which the PKMv1 acts as the authentication process, and the DiHam is responsible for key management and delivery. By transmitting securely protected and well-defined parameters for SS and BS, the two stations can mutually authenticate each other. Messages including those conveying user data and authentication parameters can be then more securely delivered.

Real-time systems like pervasive computing have to complete executing a task within the predetermined time while ensuring that the execution results are logically correct. Such systems require intelligent scheduling methods that can adequately promptly distribute the given tasks to a processor(s). In this paper, we propose LSTR (Least Slack Time Rate first), a new and simple scheduling algorithm, for a multi-processor environment, and demonstrate its efficient performance through various tests.

E-mail spam is no more garbage but risk since it recently includes virus attachments and spyware agents which make the recipients' system ruined, therefore, there is an emerging need for spam detection. Many spam detection techniques based on machine learning techniques have been proposed. As the amount of spam has been increased tremendously using bulk mailing tools, spam detection techniques should counteract with it. To cope with this, parameters optimization and feature selection have been used to reduce processing overheads while guaranteeing high detection rates. However, previous approaches have not taken into account feature variable importance and optimal number of features. Moreover, to the best of our knowledge, there is no approach which uses both parameters optimization and feature selection together for spam detection. In this paper, we propose a spam detection model enabling both parameters optimization and optimal feature selection; we optimize two parameters of detection models using Random Forests (RF) so as to maximize the detection rates. We provide the variable importance of each feature so that it is easy to eliminate the irrelevant features. Furthermore, we decide an optimal number of selected features using two methods; (i) only one parameters optimization during overall feature selection and (ii) parameters optimization in every feature elimination phase. Finally, we evaluate our spam detection model with cost-sensitive measures to avoid misclassification of legitimate messages, since the cost of classifying a legitimate message as a spam far outweighs the cost of classifying a spam as a legitimate message. We perform experiments on Spambase dataset and show the feasibility of our approaches.

Service composition is an effective approach for large-scale multimedia delivery. In previous works, user requirement is represented as one fixed functional path which is composed of several functional components in a certain order. Actually, there may be several functional paths (deliver different quality level multimedia data, e.g., image pixel, frame rate) that can meet one request. And due to the diversity of devices and connections in pervasive environment, system should choose a suitable media quality delivery path in accordance with context, instead of one fixed functional path. This paper presents a deep study of multimedia delivery problem and proposes an on-line algorithm LDPath and an off-line centralized algorithm LD/RPath respectively. LDPath aims at delivering multimedia data to end user with lowest delay by choosing services to build delivery paths hop-by-hop, which is adapted to the unstable open environment. And LD/RPath is developed for a relatively stable environment, which generates delivery paths according to the trade-off between delay and reliability metrics, because the service reliability is also an important fact in such scenario. Experimental results show that both algorithms have good performance with low overhead to the system.

RDF data can be analyzed with various query languages such as SPARQL. However, due to their nature these query languages do not support fuzzy queries that would allow us to extract a broad range of additional information. In this article we present a new method that transforms the information presented by subject-relationobject relations within RDF data into Activation Patterns. These patterns represent a common model that is the basis for a number of sophisticated analysis methods such as semantic relation analysis, semantic search queries, unsupervised clustering, supervised learning or anomaly detection. In this article, we explain the Activation Patterns concept and apply it to an RDF representation of the well known CIA World Factbook.

Ontology evaluation is an integral and important part of the ontology development process. Errors in ontologies could be catastrophic for the information system based on those ontologies. As per our experiments, the existing ontology evaluation systems were unable to detect many errors (like, circulatory error in class and property hierarchy, common class and property in disjoint decomposition, redundancy of sub class and sub property, redundancy of disjoint relation and disjoint knowledge omission) as defined in the error taxonomy. We have formulated efficient algorithms for the evaluation of these and other errors as per the extended error taxonomy. These algorithms are implemented (named as OntEval) and the implementations are used to evaluate well-known ontologies including Gene Ontology (GO), WordNet Ontology and OntoSem. The ontologies are indexed using a variant of already proposed scheme Ontrel. A number of errors and warnings in these ontologies have been discovered using the OntEval. We have also reported the performance of our implementation, OntEval.

The user experience of any software or website consists of elements from the conceptual to the concrete level. These elements of user experience assist in the design and development of user interfaces. On the other hand, ontologies provide a framework for computable representation of user interface elements and underlying data. This paper discusses strategies of introducing ontologies at different user interface layers adapted from user experience elements. These layers range from abstract levels (e.g. User needs/Application Objectives) to concrete levels (e.g. Application User Interface) in terms of data representation. The proposed ontological framework enables device independent, semi-automated GUI construction which we will demonstrate at a personal information management example.

Patient information in health care systems mostly consists of textual data, and free text in particular makes up a significant amount of it. Information retrieval systems that concentrate on these text types have to deal with the different challenges these medical free texts pose to achieve an acceptable performance. This paper describes the evaluation of four different types of information retrieval strategies: keyword search, search performed by a medical domain expert, a semantic based information retrieval tool, and a purely statistical information retrieval method. The different methods are evaluated and compared with respect to its appliance in medical health care systems.

Retrieving information or discovering knowledge from a well organized data center in general is requested to be familiar with its schema, structure, and architecture, which against the inherent concept and characteristics of cloud environment. An effective approach to retrieve desired information or to extract useful knowledge is an important issue in the emerging information/knowledge cloud. In this paper, we propose an ontology-based agent generation framework for information retrieval in a flexible, transparent, and easy way on cloud environment. While user submitting a flat-text based request for retrieving information on a cloud environment, the request will be automatically deduced by a Reasoning Agent (RA) based on predefined ontology and reasoning rule, and then be translated to a Mobile Information Retrieving Agent Description File (MIRADF) that is formatted in a proposed Mobile Agent Description Language (MADF). A generating agent, named MIRA-GA, is also implemented to generate a MIRA according to the MIRADF. We also design and implement a prototype to integrate these agents and show an interesting example to demonstrate the feasibility of the architecture.

Vehicular Networks, including Vehicular Adhoc Networks (VANETs) and Vehicular Sensor Networks (VSNs), stimulate a brand new variety of services, ranging from driver safety services, traffic information and warnings regarding traffic jams and accidents, to providing weather or road condition, parking availability, and advertisement. 3G networks and sophisticated Intelligent Transportation Systems (ITS), including deploying costly roadside base stations, can indeed be used to offer such services, but these come with a cost, both at network and hardware levels. In this paper we introduce Cooperation as a service (CaaS): A novel architecture that will allow providing a set of services for free and without any additional infrastructure, by taking advantage of Vehicle-to-Vehicle communications. CaaS uses a hybrid publish/subscribe mechanism where the driver (or subscriber) expresses his interests regarding a service (or a set of services) and where cars having subscribed to the same service will cooperate to provide the subscriber with the necessary information regarding the service he subscribed to, by publishing this information in the network. CaaS structures the network into clusters, and uses Content Based Routing (CBR) for intra-cluster communications and geographic routing for inter-cluster communications.

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Tensions à l'Université Lyon-3 : la classe politique condamne les attaques contre Yaël Braun-Pivet

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Avec l'Arizona, Donald Trump a désormais remporté la totalité des sept États clés

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Netanyahu s’est entretenu 3 fois avec Trump depuis sa réélection à propos de la "menace iranienne"

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Moyen-Orient : Israël visé par des drones et des missiles. Lourd bilan à Gaza et au Liban

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Des scientifiques découvrent un "troisième état" entre la vie et la mort

No Comment : commémoration du 106e anniversaire de l'Armistice 

No Comment : des couronnes de coquelicots pour le Dimanche du Souvenir 

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Serbie : des manifestants demandent la démission du gouvernement après le drame de Novi Sad