Translating the legislation or regulations of a country, company or university into English requires certain skills and know-how. This post lists five things your translator should know when translating legislation into English. 1. How to apply English drafting conventions Conventions on headings, numbering, referencing and capitalisation differ from one legal language to another. For instance, […]

We describe the design of a mobile collaborative tool that helps teams managing critical computing infrastructures in organizations, a task that is usually designated Business Continuity Management. The design process started with a requirements definition phase based on interviews with professional teams. The elicited requirements highlight four main concerns: collaboration support, knowledge management, team performance, and situation awareness. Based on these concerns, we developed a data model and tool supporting the collaborative update of Situation Matrixes. The matrixes aim to provide an integrated view of the operational and contextual conditions that frame critical events and inform the operators' responses to events. The paper provides results from our preliminary experiments with Situation Matrixes.

Advances in mobile technologies are opening new possibilities to support collaborative activities through mobile devices. Unfortunately, mobile collaborative systems have been difficult to conceive, design and implement. These difficulties are caused in part by their unclear requirements and developers' lack of experience with this type of systems. However, several requirements involved in the collaborative back-end of these products are recurrent and should be considered in every development. This paper introduces a characterization of mobile collaboration and a framework that specifies a list of general requirements to be considered during the conception and design of a system in order to increase its probability of success. This framework was used in the development of two mobile collaborative systems, providing developers with a base of back-end requirements to aid system design and implementation. The systems were positively evaluated by their users.

Small and Medium Enterprises (SMEs) face new challenges in the global market as customers require more complete and flexible solutions and continue to drastically reduce the number of suppliers. SMEs are trying to address these challenges through cooperation within collaborative enterprise networks (CENs). Human aspects constitute a fundamental issue in these networks as people, as opposed to organizations or Information Technology (IT) systems, cooperate. Since there is a lack of empirical studies on the role of human factors in IT-supported collaborative enterprise networks, this paper addresses the major human aspects encountered in this type of organization. These human aspects include trust issues, knowledge and know-how sharing, coordination and planning activities, and communication and mutual understanding, as well as their influence on the business processes of CENs supported by IT tools. This paper empirically proves that these aspects constitute key factors for the success or the failure of CENs. Two case studies performed on two different CENs in Switzerland are presented and the roles of human factors are identified with respect to the IT support systems. Results show that specific human factors, namely trust and communication and mutual understanding have to be well addressed in order to design and develop adequate software solutions for CENs.

This paper focuses on improving the management of New-Product Development (NPD) processes within the particular context of a cluster of enterprises that cooperate through a network of intra- and inter-firm relations. Ceramic tile design chains have certain singularities that condition the NPD process, such as the lack of a strong hierarchy, fashion pressure or the existence of different origins for NPD projects. We have studied these particular circumstances in order to tailor Product Life-cycle Management (PLM) tools and some other management mechanisms to fit suitable sectoral reference models. Special emphasis will be placed on PLM templates for structuring and standardizing projects, and also on the roles involved in the process.

This work describes a methodology that supports the design and implementation of software modules, which represent the individual and collaborative three-dimensional interaction process phases. The presented methodology integrates three modeling approaches: Petri Nets, a collaborative manipulation model based on the combination of single user interaction techniques taxonomy, and object-oriented programming concepts. The combination of these elements allows for the description of interaction tasks, the sequence of interaction processes being controlled by Petri Nets with the codes generated automatically. By the integration of these approaches, the present work addresses not only the entire development cycle of both individual and collaborative three-dimensional interaction, but also the reuse of developed interaction blocks in new virtual environment projects.

With the emergence of the Web 2.0 phenomena, technology-assisted social networking has become the norm. The potential of social software for collaborative learning purposes is clear, but as yet there is little evidence of realisation of the benefits. In this paper we consider Information and Communication Technology student attitudes to collaboration and via two case studies the extent to which they exploit the use of wikis for group collaboration. Even when directed to use a particular wiki designed for the type of project they are involved with, we found that groups utilized the wiki in different ways according to the affordances ascribed to the wiki. We propose that the integration of activity theory with an affordances perspective may lead to improved technology, specifically Web 2.0, assisted collaboration.

Computer Supported Collaborative Learning could highly impact education around the world if the proper Collaborative Learning tools are set in place. In this paper we describe the design of a collaborative learning activity for teaching Chemistry to Chilean students. We describe a PDA-based software tool that allows teachers to create workgroups in their classrooms in order to work on the activity. The developed software tool has three modules: one module for teachers, which runs on a PC and lets them create the required pedagogical material; second, there is a PDA module for students which lets them execute the activity; finally, a third module allows the teacher set workgroups and monitor each workgroup during the activity.

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.

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.

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.

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.

On semble s'acheminer vers une vague En Marche de forte magnitude aux prochaines Législatives. Si Les Républicains espèrent limiter la casse, c'est à dire avec un perte d'une centaine de députés. L'enjeu de LR, c'est l'après avec en ligne de mire, un...

J’ai commencé à bloguer en 2006, je ne compte plus le nombre de billets que j’ai pu faire sur la montée inexorable de l’abstention élection après élection. On a pu croire que la montée en puissance des réseaux sociaux aller faire émerger une démocratie...

Mine de rien les Gilets jaunes, quoiqu'on en pense, on réussit à faire bouger les lignes sur des éléments qu'on nous disait impossible jusqu'à présent. Au delà de certaines applications qui peuvent être laissées au débat, en matière de pouvoir d'achat,...

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

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

No Comment : funérailles collectives au Liban

Donald Trump confie à Elon Musk et Vivek Ramaswamy "l'efficacité gouvernementale"

No Comment : les universités en crise en Argentine 

Improving website structures is the main task of a website designer. In recent years, numerous web engineering researchers have investigated navigation recommendation systems. Page recommendation systems are critical for mobile website navigation. Accordingly, we propose a smart and adaptive navigation recommendation system based on reinforcement learning. In this system, user navigation history is used as the input for reinforcement learning model. The model calculates a surf value for each page of the website; this value is used to rank the pages. On the basis of this ranking, the website structure is modified to shorten the user navigation path length. Experiments were conducted to evaluate the performance of the proposed system. The results revealed that user navigation paths could be decreased by up to 50% with training on 12 months of data, indicating that users could more easily find a target web page with the help of the proposed adaptive navigation recommendation system.

1. John Krasinski named People magazine's 2024 Sexiest Man Alive  CTV News
2. Sexiest Man Alive John Krasinski on His 'Beautiful Life' – and Wallpapering His House with His Sizzling PEOPLE Cover  PEOPLE
3. Krasinski thought he was being 'punked'  CTV News Calgary
4. John Krasinski Reveals Wife Emily Blunt's Hilarious Response to His Sexiest Man Alive Title - E! Online  E! NEWS
5. Emily Blunt reacts after husband is named 2024 Sexiest Man Alive  The Independent

1. Trump says Elon Musk, Vivek Ramaswamy will lead the Department of Government Efficiency  The Globe and Mail
2. Why is Elon Musk becoming Donald Trump's efficiency adviser?  BBC.com
3. Elon Musk and Vivek Ramaswamy will lead new 'Department of Government Efficiency' in Trump administration  CTV News
4. George Conway: Musk, Ramaswamy to lead ‘nonexistent department’  The Hill

Online journal dedicated to nursing informatics

The operation of supply chain finance faces various risks, therefore, studying the operational risks of supply chain finance and corresponding preventive measures is of great significance. Firstly, classify the types of operational risks in supply chain finance. Secondly, based on the risk classification results, the decision tree method is used to evaluate the operational risks of supply chain finance. Finally, based on the risk assessment results, targeted risk prevention measures for supply chain finance operations are proposed, such as strengthening supplier management, optimising logistics and warehouse management, risk analysis and monitoring, and strengthening information security and data protection. The case analysis results show that the accuracy of the evaluation results of this method is higher, and the risk coefficient has been significantly reduced after applying this method, indicating that it can effectively reduce supply chain risk.

This paper aims to analyse the effectiveness of cost control oriented enterprise financial risk management. Firstly, it analyses the importance of enterprise financial risk management. Secondly, the position of cost control in enterprise financial risk management was analysed. Cost control can be used to reduce the operating costs of enterprises, improve their profitability, and thus reduce the financial risks they face. Finally, a corporate financial risk management strategy is constructed from several aspects: establishing a sound risk management system, predicting and responding to various risks, optimising fund operation management, strengthening internal control, and enhancing employee risk awareness. The results show that after applying the proposed management strategy, the enterprise performs well in cost control oriented enterprise financial risk management, with a cost accounting accuracy of 95% and an audit system completeness of 90%. It can also help the enterprise develop emergency plans and provide comprehensive risk management strategy coverage.