Noel Cressie and Christopher WikleHardcover: 624 pagesYear: 2011Publisher: John WileyISBN-13: 978-0471692744Here is the new reference book about spatial and spatio-temporal statistical modeling! No...

Statistics for Spatio-Temporal Data

Arrangements involving portable devices (e.g., smartphones and tablet computers) are disclosed. One arrangement enables a content creator to select software with which that creator's content should be rendered—assuring continuity between artistic intention and delivery. Another utilizes a device camera to identify nearby subjects, and take actions based thereon. Others rely on near field chip (RFID) identification of objects, or on identification of audio streams (e.g., music, voice). Some technologies concern improvements to the user interfaces associated with such devices. Others involve use of these devices in connection with shopping, text entry, sign language interpretation, and vision-based discovery. Still other improvements are architectural in nature, e.g., relating to evidence-based state machines, and blackboard systems. Yet other technologies concern use of linked data in portable devices—some of which exploit GPU capabilities. Still other technologies concern computational photography. A great variety of other features and arrangements are also detailed.

Smartphone-based methods and systems

Autonomous robotic systems are complex, hybrid, and often safety-critical; this makes their formal specification and verification uniquely challenging. Though commonly used, testing and simulation alone are insufficient to ensure the correctness of, or provide sufficient evidence for the certification of, autonomous robotics. Formal methods for autonomous robotics has received some attention in the literature, but no resource provides a current overview. This paper systematically surveys the state-of-the-art in formal specification and verification for autonomous robotics. Specially, it identifies and categorises the challenges posed by, the formalisms aimed at, and the formal approaches for the specification and verification of autonomous robotics.

Formal Specification and Verification of Autonomous Robotic Systems: A Survey

This paper presents learning analytics as a mean to improve students’ learning. Most learning analytics tools are developed by in-house individual educational institutions to meet the specific needs of their students. Learning analytics is defined as a way to measure, collect, analyse and report data about learners and their context, for the purpose of understanding and optimizing learning. The paper concludes by highlighting framework of learning analytics in order to improve personalised learning. In addition, it is an endeavour to define the characterising features that represents the relationship between learning analytics and personalised learning environment. The paper proposes that learning analytics is dependent on personalised approach for both educators and students. From a learning perspective, students can be supported with specific learning process and reflection visualisation that compares their respective performances to the overall performance of a course. Furthermore, the learners may be provided with personalised recommendations for suitable learning resources, learning paths, or peer students through recommending system. The paper’s contribution to knowledge is in consider ing personalised learning within the context framework of learning analytics

/pdf/demystifying-learning-analytics-in-personalised-learning-4fqirnindg.pdf

Demystifying Learning Analytics in Personalised Learning

data.europeana.eu is an ongoing effort of making Europeana metadata available as Linked Open Data on the Web. It allows others to access metadata collected from Europeana data providers via standard Web technologies. The data are represented in the Europeana Data Model (EDM) and the described resources are addressable and dereferencable by their URIs. Links between Europeana resources and other resources in the Linked Data Web will enable the discovery of semantically related resources. We developed an approach that allows Europeana data providers to opt for their data to become Linked Data and converts their metadata to EDM, benefiting from Europeana efforts to link them to semantically related resources on the Web. With that approach, we produced a first Linked Data version of Europeana and published the resulting datasets on the Web. We also gained experiences with respect to EDM, HTTP URI design, and RDF store performance and report them in this paper.

/pdf/data-europeana-eu-the-europeana-linked-open-data-pilot-2aodmb374j.pdf

data.europeana.eu: the europeana linked open data pilot

Kravcik, Milos [Hrsg.]; Santos, Olga C. [Hrsg.]; Boticario, Jesus G. [Hrsg.]: PALE 2014. Personalization approaches in learning environments. Aalborg 2014, S. 55-62. - (CEUR Workshop Proceedings; 1181)
Padagogische Teildisziplin: Medienpadagogik;

/pdf/personalized-web-learning-merging-open-educational-resources-3mwq06lrh0.pdf

Personalized Web Learning: Merging Open Educational Resources into Adaptive Courses for Higher Education

With the continuously growing amount of structured data available on the Semantic Web there is an increasing desire to replicate such data to mobile devices. This enables services and applications to operate independently of the network connection quality. Traditional replication strategies cannot be properly applied to mobile systems because they do not adopt to changing user information needs, and they do not consider the technical, environmental, and infrastructural restrictions of mobile devices. Therefore, it is reasonable to consider contextual information, gathered from physical and logical sensors, in the replication process, and replicate only data that are actually needed by the user. In this paper we present a framework that uses Semantic Web technologies to build comprehensive descriptions of the user's information needs based on contextual information, and employs these descriptions to selectively replicate data from external sources. In consequence, the amount of replicated data is reduced, while a maximum share of relevant data are continuously available to be used by applications, even in situations with limited or no network connectivity.

Context-driven RDF data replication on mobile devices

The IMS Learning Design (IMS LD) specification offers a language for modeling teaching and learning situations and flows. The specification contains great complexity, which represents a high entrance barrier to its use. To lower this entrance barrier to Learning Design, easy-to-handle software is needed that translates from the language used by instructional practitioners to IMS LD. This paper describes an approach for performing this translation. First, an analysis is described that was used for deriving typical uses of IMS LD Level B properties and conditions. Second, the resulting cases and translation transactions are presented. It is hypothesized that a wizard allows practitioners access to Level B functionalities even though the wizard reduces the complexity of the specification.

Making sense of IMS learning design level B: from specification to intuitive modeling software

With the continuously growing amount of structured data available on the Semantic Web there is an increasing desire to replicate such data to mobile devices. This enables services and applications to operate independently of the network connection quality. Traditional replication strategies cannot be properly applied to mobile systems because they do not adopt to changing user information needs, and do not consider the technical, environmental, and infrastructural restrictions of mobile devices. Therefore, it is reasonable to consider contextual information, gathered from physical and logical sensors, in the replication process, and replicate only data that are actually needed by the user. In this paper we present a framework that uses Semantic Web technologies to build comprehensive descriptions of the user's information needs based on contextual information, and employs these descriptions to selectively replicate data from external sources. In consequence, the amounts of replicated data are reduced, while a maximum share of relevant data are continuously available to be used by applications, even in situations with limited or no network connectivity.

/pdf/a-framework-for-context-driven-rdf-data-replication-on-1ptepktp76.pdf

A framework for context-driven RDF data replication on mobile devices

Horbach, Matthias [Hrsg.]: Informatik angepasst an Mensch, Organisation und Umwelt : Tagung vom 16. – 20. September 2013 in Koblenz. Bonn : Gesellschaft fur Informatik e.V. 2013, 6 S.. - (Lecture Notes in Informatics (LNI) - Proceedings; P-220)
Padagogische Teildisziplin: Medienpadagogik;

A Pedagogical Ontology as a Playground in Adaptive Elearning Environments.

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