A common language

Learning foreign languages in the 21st century is a human necessity, a prerequisite for personal and professional success, an activity impossible to avoid. In addition, learning English, considered a lingua franca, a language so widely spread in the virtual world, mass media, advertising, music, TV shows, etc. can be easy, entertaining and accessible. Starting from the topic of this workshop, based on my own experience as a Foreign Language Teacher and backed up by specialised courses for teachers of English, this paper aims to review, in a development focused manner, several authentic materials that teachers can use in class and to discuss the variety of sources that students can resort to and use individually. On the one hand, teachers can tailor articles or stories from blogs, company websites, brochures, newspapers, magazines, etc, which, although not written for academic purposes, do contain real life situations, case studies, the genuine vocabulary of a specific field. This article will provide practical examples of online texts modified for the level of the students and the variety of activities derived from this adaptation, thus, matching reading, writing, speaking or vocabulary activities. On the other hand, students, fond of and familiar with the virtual world, and who possess the necessary "habits of mind associated with these technologies" (Beetham and Sharpe, "An Introduction to Rethinking Pedagogy for a Digital Age", 2007: 5) should be encouraged to use the Worldwide Web wisely in order to improve their language skills. Mobile apps for language learning (such as: http://freerice.com or https://www.duolingo.com/) or the inputs given by http://www.bbc.co.uk/learningenglish/ can be used by students on their own, in the comfort of their home. This paper will analyse the two apps and some Podcasts that can help learners to correct their pronunciation, giving them the confidence they need to express themselves in public.

Online social networks have been typically created for convenience--so they haven't been built from the ground up with security in mind. They often have confusing privacy settings and are susceptible to various kinds of attacks that exploit users' trust and privacy. In this article, the authors discuss security pitfalls in today's social networks, briefly introducing common attack methods. They implemented a proof-of-concept Facebook app, which is actually a harmless malware that uses common attack methods to demonstrate the vulnerability of online social networks. Although today's online social networks commonly offer users a variety of security settings, users tend to trust the information obtained from online social networks regardless of the settings. This kind of user mentality can be more crucial than technical aspects in determining the level of security in online social networks.

Game-based learning is gaining popularity in language education. For the present study, three games were developed with a central focus on intercultural interaction to be played internationally in dyads or small groups using Video-Communication (VC) tools or a Virtual World (VW). The interactions were carried out in Spanish as a Lingua Franca (LF) between 32 university students over a period of three weeks. Different sources of data were gathered in order to study how games, played in an intercultural setting in VWs and VC, influence or not key affective variables in language learning. Initial results of the final questionnaires show that the interaction games did boost students’ engagement in virtual exchanges, but results were more promising for the VC than the VW condition.

In today's online social networking, one can Google social network and stumble upon an array of different results. Each of these choices is often associated with a common cause for people to network. The majority of today's social networks are focused more towards teenagers and young adults as a virtual ldquohangoutrdquo and discussion area. However, there is a lack in one crucial area of social networking development and that is the medical/healthcare industry. One demographic not directly accounted for in the social networking age is people with the need for acquiring medical or healthcare related information and for connecting with others on this level. In addition, Web based social networks are limited to access restrictions. Users are usually required to access from a PC or laptop. This problem is slowly being taken care of with the emergence of mobile social networking. Milestone mobile devices such as the Apple iPhone and the Google/HTC G1 phone have helped jump start this transition. The paper looks into the new aspects how to design a special wireless mobile system (mCare) based on social networking platform in healthcare.

Maintaining data availability is one of the biggest challenges in decentralized online social networks (DOSNs). The existing work often assumes that the friends of a user can always contribute to the sufficient storage capacity to store all data. However, this assumption is not always true in today's online social networks (OSNs) due to the fact that nowadays the users often use the smart mobile devices to access the OSNs. The limitation of the storage capacity in mobile devices may jeopardize the data availability. Therefore, it is desired to know the relation between the storage capacity contributed by the OSN users and the level of data availability that the OSNs can achieve. This paper addresses this issue. In this paper, the data availability model over storage capacity is established. Further, a novel method is proposed to predict the data availability on the fly. Extensive simulation experiments have been conducted to evaluate the effectiveness of the data availability model and the on-the-fly prediction.

While highly successful, today's online social networks (OSNs) have made a conscious decision to sacrifice privacy for availability and centralized control. Unfortunately, tradeoffs in this walled garden architecture naturally pit the economic interests of OSN providers against the privacy goals of OSN users, a battle that users cannot win. While some alternative OSN designs preserve user control over data, they do so by de-prioritizing issues of economic incentives and sustainability. In contrast, we believe any practical alternative to today's centralized architecture must consider incentives for providers as a key goal. In this paper, we propose a distributed OSN architecture that significantly improves user privacy while preserving economic incentives for OSN providers. We do so by using a standardized API to create a competitive provider marketplace for different components of the OSN, thus allowing users to perform their own tradeoffs between cost, performance, and privacy. We describe Polaris, a system where users leverage smartphones as a highly available identity provider and access control manager, and use application prototypes to show how it allows data monetization while limiting the visibility of any single party to users' private data.

Although today's online social networks provide some privacy controls to protect a user's shared content from other users, these controls aren't sufficiently expressive to provide fine-grained protection. Twitsper offers fine-grained control over who sees a Twitter user's messages, enabling private group communication while preserving Twitter's commercial interests.

One fundamental issue in today's Online Social Networks (OSNs) is to give users the ability to control the messages posted on their own private space to avoid that unwanted content is displayed. Up to now, OSNs provide little support to this requirement. To fill the gap, in this paper, we propose a system allowing OSN users to have a direct control on the messages posted on their walls. This is achieved through a flexible rule-based system, that allows users to customize the filtering criteria to be applied to their walls, and a Machine Learning-based soft classifier automatically labeling messages in support of content-based filtering.

Community detection is of great importance for online social network analysis. The volume, variety and velocity of data generated by today's online social networks are advancing the way researchers analyze those networks. For instance, real-world networks, such as Facebook, LinkedIn and Twitter, are inherently growing rapidly and expanding aggressively over time. However, most of the studies so far have been focusing on detecting communities on the static networks. It is computationally expensive to directly employ a well-studied static algorithm repeatedly on the network snapshots of the dynamic networks. We propose DynaMo, a novel modularity-based dynamic community detection algorithm, aiming to detect communities of dynamic networks as effective as repeatedly applying static algorithms but in a more efficient way. DynaMo is an adaptive and incremental algorithm, which is designed for incrementally maximizing the modularity gain while updating the community structure of dynamic networks. In the experimental evaluation, a comprehensive comparison has been made among DynaMo, Louvain (static) and 5 other dynamic algorithms. Extensive experiments have been conducted on 6 real-world networks and 10,000 synthetic networks. Our results show that DynaMo outperforms all the other 5 dynamic algorithms in terms of the effectiveness, and is 2 to 5 times (by average) faster than Louvain algorithm.

<p>The aim of the PotuGame proposal to give a step more on strategies already developed in previous Potu Program (Programa d’Orientació i Transició a la Universitat-UIB). For that we add a new multidisciplinary component that enables high school students, teachers and researchers from UIB to share knowledge of the research conducted using a common language or a common world. Therefore it is considered very appropriate to use the technologies related to the creation of virtual worlds, especially those aimed in online video games as a means to allow vehicle for the transmission of knowledge in an interactive and fun way increasing mass participation of all components of the teaching environment at all levels. Several experiments have been developed and that have been implemented in several virtual worlds. The final tool used was the Unreal SDK.</p>

There are many entities (or components) in a system that keeps on evolving over system states. The connection (or relationship) between entities also keep on evolving over system state, which makes series of evolving networks. Such networks can be studied over evolving state to provide system evolution information for analysis. This can be achieved with the help of hybrid mining approaches. The network rule information can be detected using network rule mining. The network subgraph information can be retrieved using network subgraph mining. The evolution information is detected using evolution mining. In this paper, we introduce a Evolution model, which is explained using two pattern-mining techniques: network evolution rule mining and network evolution subgraph mining. The first technique retrieves network evolution rules (NERs), and the second technique retrieves network evolution subgraphs (NESs). The two techniques are prototyped as two System Evolution Analytics tools that are used to do experiments on six evolving systems. We demonstrated the application of the tools for the system evolution analysis.

Electricity is one of the most widely used forms of energy. However, environmental pollution from electricity generation and the mismatch between electricity supply and demand have long been bothering economies across the world. Under this background, cross-border electricity trade provides a new direction for sustainable development. Based on the complex network approach, this paper aims to explore the structural characteristics and evolution of cross-border electricity trade networks and to figure out the factors influencing the formation of the network by using the more advanced network analysis method—ERGM. The results show that: (1) The scale of the electricity trade network is expanding, but there are still many economies not involved. (2) The centrality of the network shifts from west to east. The level of internal electricity interconnection is high in Europe, and Asian countries’ coordination role in cross-border electricity trade networks is enhanced. (3) Cross-border electricity trade helps to reduce CO2 emissions, achieve renewable energy transformation, and reduce power supply and demand mismatch. Large gaps in GDP, electricity prices, industrial structure, geographical distance and institutional distance between economies are not conducive to form the cross-border trade network, while the common language is on the contrary.

During the last two decades, two important contributions have reshaped our understanding of international trade. First, countries trade more with those with whom they share history, language, and culture, suggesting that trade is limited by information frictions. Second, countries are more likely to start exporting products that are related to their current exports, suggesting that shared capabilities and knowledge diffusion constrain export diversification. Here, we join both of these streams of literature by developing three measures of bilateral relatedness and using them to ask whether the destinations to which a country will increase its exports of a product are predicted by these forms of relatedness. The first form is product relatedness, and asks whether a country already exports many similar products to a destination. The second is importer relatedness, and asks whether the country exports the same product to the neighbors of the target destination. The third is exporter relatedness, and asks whether a country’s neighbors are already exporting the same product to the destination. We use bilateral trade data from 2000 to 2015, and a variety of controls in multiple gravity specifications, to show that countries are more likely to increase their exports of a product to a destination when they have more product relatedness, importer relatedness, and exporter relatedness. Then, we use several sample splits to explore whether the effects of these forms of relatedness are stronger for products of higher complexity, technological sophistication, and differentiation. We find that, in the case of product relatedness, the effects are stronger for differentiated, complex, and technologically sophisticated products. Also, we find the effects of common language and shared colonial past to increase with differentiation, complexity, and technological sophistication, while the effects of shared borders decrease with these three variables. These results suggest that product relatedness and common language capture dimensions of knowledge relatedness that are more important for the exchange of more sophisticated and differentiated products. These findings extend the ideas of relatedness to bilateral trade and show that the evolution of bilateral trade networks are shaped by relatedness among products, exporters, and importers.

Factors affecting binary sex evolution with respect to avoidance of vertical transmission of deleterious intracellular parasites

The paper describes a method of education and training involving off-line usage of virtual environments (VE) for task planning. When programmed tasks of a robot arm in the virtual world are developed to the satisfaction of the trainee, they are exported to a remote physical hardware, via the Internet, for the real world execution. The on-line feedback data from the robot arm and live video picture are sent back to the remote client via Internet. Development of the Remote Laboratory (RLab) system connected with a remote controlled on-line video system and the training experiments are discussed, along with some of the issues raised for telerobotics.