Abstract Seminal: Additive Semantic Content for Multimedia Streams

Technological advances such as higher network bandwidth and greater end-user computing power provide the basis for new types of media rich applications. As applications produce larger numbers of more diverse media streams, the content becomes too overwhelming to be useful in its raw form. The contribution of this work is the initial design of Seminal, a model that solves the problem of multimedia overload by enhancing multimedia streams with semantic information about their content and relationship. The goal of Seminal is to manually or automatically derive semantic meaning from a given set of media streams. When the media streams are presented, archived, or distributed between users, the semantics are used to filter the most relevant information from the entire information base. We have designed a digital classroom-based prototype to validate our assumption that semantic information can be used to allow users to interact in a media rich environment.

Power-aware data management for small devices

Pervasive computing devices such as Personal Digital Assistants (PDAs) and laptop computers are becoming increasingly ubiquitous. The future promises even more advanced devices such as digital watches, jewelry, and even clothing. However, as pervasive devices become more widely used for more advanced applications, their resource limitations are becoming more apparent. In this work, we focus on data management and power limitations. We investigate the benefit of using power-aware schemes to automatically manage content across a collection of devices and prolong data availability. We monitor the available energy supply on each device and migrate content from devices that are in danger of dying. In our simulated environment, we have found that, using intelligent techniques for data management can increase the amount of time a collection of devices remains usable by over 2 times. Furthermore, our techniques can perform autonomously, independent of user intervention

Lessons Learned Deploying a Digital Classroom

A number of university campuses have undertaken the development of digital classrooms that enable presentation of digital media and digital lecture recording. While educators from across disciplines are interested in using the facilities these classroom spaces provide, deploying the infrastructure for a digital classroom is difficult at best, even for a technically savvy person. As people from many disciplines become interested in building similar digital classroom spaces, there is a need to produce a useful set of design and implementation guidelines for determining the functionality of such a space and selecting and installing the equipment to achieve that functionality. The goal of this article is to report on the deployment of the UCSB digital classroom. By using this article as a guide, future digital classroom architects can reduce the project risk and steepness of the deployment curve

A Framework For Creating Customized Multi-Modal Interfaces For XML Documents

The eXtensible Markup Language(XML) is emerging as a new way to store and communicate data. Even though its primary application is as the future of the World Wide Web, it can be used in a variety of situations to structure electronic data. As XML becomes ubiquitous, there is a need to develop tools to allow users to view, navigate, and modify the underlying XML data via a high-level, multimodal interface. Moreover, because XML can be used in a variety of situations, the tools must allow a user to access the data via non-traditional interfaces. The web, eCommerce, and digital classrooms are all possible applications for XML. This paper presents a framework for developing multi-modal tools to view, navigate, and modify XML structures. 1. MOTIVATION XML[3] is a powerful language that enables a user to store and communicate semi-structured data. In addition to being the future of the World Wide Web[2], XML has the potential for use in distance learning[4] as well as business-tobusiness, ..

Automating energy management in green homes

Homes powered fully or partially by renewable sources such as solar are becoming more widely adopted, however energy management strategies in these environments are lacking. This paper presents the first results of a study that explores home automation techniques for achieving better utilization of energy generated by renewable technologies. First, using a network of off-the-shelf sensing devices, we observe that energy generation and consumption in an off-grid home is both variable and predictable. Moreover, we find that reactive energy management techniques are insufficient to prevent critical battery situations. We then present a recommendation based system for helping users to achieve better utilization of resources. Our study demonstrates the feasibility of three recommendation components: an early warning system that allows users of renewable technologies to make more conservative decisions when energy harvested is predicted to be low; a task rescheduling system that advises users when high-power appliances such as clothes dryers should be run to optimize overall energy utilization; and an energy conservation system that identifies sources of energy waste and recommends more conservative usage. Categories and Subject Descriptors H.1.2 [Models and Principles]: User/Machine Systems— human factor