Towards an Emergent Semantic Web

In his in uential article about the evolution of the Web, Berners-Lee [1] envisions a Semantic Web in which humans and computers alike are capable of understanding and processing information. This vision is yet to materialize. The main obstacle for the Semantic Web vision is that in today's Web meaning is rooted most often not in formal semantics, but in natural language and, in the sense of semiology, emerges not before interpretation and processing. Yet, an automated form of interpretation and processing can be tackled by precisiating raw natural language. To do that, Web agents extract fuzzy grassroots ontologies through induction from existing Web content. Inductive fuzzy grassroots ontologies thus constitute organically evolved knowledge bases that resemble automated gradual thesauri, which allow precisiating natural language [2]. The Web agents' underlying dynamic, self-organizing, and best-effort induction, enable a sub-syntactical bottom up learning of semiotic associations. Thus, knowledge is induced from the users' natural use of language in mutual Web interactions, and stored in a gradual, thesauri-like lexical-world knowledge database as a top-level ontology, eventually allowing a form of computing with words [3]. Since when computing with words the objects of computation are words, phrases and propositions drawn from natural languages, it proves to be a practical notion to yield emergent semantics for the Semantic Web. In the end, an improved understanding by computers on the one hand should upgrade human- computer interaction on the Web, and, on the other hand allow an initial version of human- intelligence amplification through the Web.

Unanticipated Partial Behavioral Reflection: Adapting Applications at Runtime

Dynamic, unanticipated adaptation of running systems is of interest in a variety of situations, ranging from functional upgrades to on-the-fly debugging or monitoring of critical applications. In this paper we study a particular form of computational reflection, called unanticipated partial behavioral reflection, which is particularly well-suited for unanticipated adaptation of real-world systems. Our proposal combines the dynamicity of unanticipated reflection, i.e. reflection that does not require preparation of the code of any sort, and the selectivity and efficiency of partial behavioral reflection. First, we propose unanticipated partial behavioral reflection which enables the developer to precisely select the required reifications, to flexibly engineer the metalevel and to introduce the meta behavior dynamically. Second, we present a system supporting unanticipated partial behavioral reflection in Squeak Smalltalk, called Geppetto, and illustrate its use with a concrete example of a web application. Benchmarks validate the applicability of our proposal as an extension to the standard reflective abilities of Smalltalk.

Dangers of ‘Facebook Login’ for Mobile Apps: Is There a Price Tag for Social Information?

Social networks offer horizontal integration for any mobile platform providing app users with a convenient single sign-on point. Nonetheless, there are growing privacy concerns regarding its use. These vulnerabilities trigger alarm among app developers who fight for their user base: While they are happy to act on users’ information collected via social networks, they are not always willing to sacrifice their adoption rate for this goal. So far, understanding of this trade-off has remained ambiguous. To fill this gap, we employ a discrete choice experiment to explore the role of Facebook Login and investigate the impact of accompanying requests for different information items / actions in the mobile app adoption process. We quantify users’ concerns regarding these items in monetary terms. Beyond hands-on insights for providers, our study contributes to the theoretical discourse on the value of privacy in the growing world of Social Media and mobile web.

Growth in Virologically Suppressed HIV Positive Children on Antiretroviral Therapy: Individual and Population-Level References

BACKGROUND Combination antiretroviral therapy (ART) suppresses viral replication in HIV-infected children. The growth of virologically suppressed children on ART has not been well documented. We aimed to develop dynamic reference curves for weight-for-age z scores (WAZ) and height-for-age z scores (HAZ). RESULTS A total of 4,876 children were followed for 7,407 person-years. Analyses were stratified by baseline z-scores and age, which were the most important predictors of growth response. The youngest children showed the most pronounced increase in weight and height initially but catch-up growth stagnated after 1-2 years. Three years after starting ART, WAZ ranged from -2.2 (95% Prediction interval -5.6 to 0.8) in children with baseline age "5 years and z-score "-3 to 0.0 (-2.7 to 2.4) in children with baseline age "2 years and WAZ "-1. For HAZ the corresponding range was -2.3 (-4.9 to 0.3) in children with baseline age"5 years and z-score "-3 to 0.3 (-3.1 to 3.4) in children with baseline age 2-5 years and HAZ "-1. CONCLUSIONS We have developed an online tool to calculate reference trajectories in fully suppressed children. The web application could help to define 'optimal' growth response and identify children with treatment failure.

Timely Reporting and Interactive Visualization of Animal Health and Slaughterhouse Surveillance Data in Switzerland

The reporting of outputs from health surveillance systems should be done in a near real-time and interactive manner in order to provide decision makers with powerful means to identify, assess, and manage health hazards as early and efficiently as possible. While this is currently rarely the case in veterinary public health surveillance, reporting tools do exist for the visual exploration and interactive interrogation of health data. In this work, we used tools freely available from the Google Maps and Charts library to develop a web application reporting health-related data derived from slaughterhouse surveillance and from a newly established web-based equine surveillance system in Switzerland. Both sets of tools allowed entry-level usage without or with minimal programing skills while being flexible enough to cater for more complex scenarios for users with greater programing skills. In particular, interfaces linking statistical softwares and Google tools provide additional analytical functionality (such as algorithms for the detection of unusually high case occurrences) for inclusion in the reporting process. We show that such powerful approaches could improve timely dissemination and communication of technical information to decision makers and other stakeholders and could foster the early-warning capacity of animal health surveillance systems.

Evaluation of a web-based application versus conventional instruction in the undergraduate curriculum of fixed prosthodontics

The present study aims to investigate the implications of web-based delivery of identical learning content for time efficiency and students' performance, as compared to conventional textbook resources.

Does the Use of Mobile Devices (Tablets and Smartphones) Affect Stated Choice Behavior in Web Surveys? An Application to Environmental Valuation

Web surveys are becoming increasingly popular in survey research. Compared with face-to-face, telephone and mail surveys, web surveys may contain a different and new source of measurement error and bias: the type of device that respondents use to answer the survey questions. To the best of our knowledge, this is the first study that tests whether the use of mobile devices affects survey characteristics and stated preferences in a web-based choice experiment. The web survey was carried out in Germany with 3,400 respondents, of which 12 per cent used a mobile device (i.e. tablet or smartphone), and comprised a stated choice experiment on externalities of renewable energy production using wind, solar and biomass. Our main finding is that survey characteristics such as interview length and acquiescence tendency are affected by the device used. In contrast to what might be expected, we find that, compared with respondents using desktop computers and laptops, mobile device users spent more time to answer the survey and are less likely to be prone to acquiescence bias. In the choice experiment, mobile device users tended to be more consistent in their stated choices, and there are differences in willingness to pay between both subsamples.