56Computer Rover: Scalable Location-Aware Computing C onsider a group touring the museums in Washington, D.C. The group arrives at a registration point, where each person receives a handheld device with audio, video, and wireless communication capabilities-an off-the-shelf PDA available in the market today. A wireless-based system tracks the location of these devices and presents relevant information about displayed objects as the user moves through the museum. Users can query their devices for maps and optimal routes to objects of interest. They can also use the devices to reserve and purchase tickets to museum events later in the day. The group leader can send messages to coordinate group activities.The part of this system that automatically tailors information and services to a mobile user's location is the basis for location-aware computing. This computing paradigm augments the more traditional dimensions of system awareness, such as time-, user-, and device-awareness. All the technology components to realize location-aware computing are available in the marketplace today. What has hindered the widespread deployment of location-based systems is the lack of an integration architecture that scales with user populations.We developed Rover technology to meet this need. 1 We have completed the initial implementation of a system based on it and have validated its underlying software architecture, which achieves system scalability through fine-resolution, application-specific resource scheduling at the servers and network. ROVER ARCHITECTURERover technology tracks the location of system users and dynamically configures application-level information to different link-layer technologies and client-device capabilities. A Rover system represents a single domain of administrative control, managed and moderated by a Rover controller. Figure 1 shows a large application domain partitioned into multiple administrative domains, each with its own Rover system-much like the Internet's Domain Name System. 2End users interact with the system through Rover client devices-typically wireless handheld units with varying capabilities for processing, memory and storage, graphics and display, and network interfaces. Rover maintains a profile for each device, identifying its capabilities and configuring content accordingly. Rover also maintains end-user profiles, defining specific user interests and serving content tailored to them.A wireless access infrastructure provides connectivity to the Rover clients. In the current implementation, we have defined a technique to determine location based on certain properties of the wireless access infrastructure. Although Rover can leverage such properties of specific air interfaces, 1 its location management technique is not tied to a particular wireless technology. Moreover, different wireless interfaces can coexist in a single Rover system or in different domains of a multi-Rover system. Software radio technology 3 offers a way to integrate the different interfaces into a single device. This wo...

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Abstract. 3D-ultrasound can become a new, fast, non-radiative, noninvasive, and inexpensive tomographic medical imaging technique with unique advantages for the localization of vessels and tumors in soft tissue (spleen, kidneys, liver, breast etc.). In general, unlike the usual 2D-ultrasound, in the 3D-case a complete volume is covered with a whole series of cuts, which would enable a 3D reconstruction and visualization.In the last two decades, many researchers have attempted to produce systems that would allow the construction and visualization of threedimensional (3-D) images from ultrasound data. There is a general agreement that this development represents a positive step forward in medical imaging, and clinical applications have been suggested in many different areas. However, it is clear that 3-D ultrasound has not yet gained widespread clinical acceptance, and that there are still important problems to solve before it becomes a common tool.

Abstract. Context-aware computing involves the automatic tailoring of information and services based on the current location of the user. In this paper, we describe our experience in implementing Rover, a system that enables location-based services, as well as the traditional time-aware, user-aware and device-aware services. To achieve system scalability to very large client sets, Rover servers are implemented in an "action-based" concurrent software architecture that enables finegrained application-specific scheduling of tasks. We have demonstrated its feasibility through implementations for both outdoor and indoor environments on multiple platforms.

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