Computing Upper and Lower Bounds on Likelihoods in Intractable Networks

We present techniques for computing upper and lower bounds on the likelihoods of partial instantiations of variables in sigmoid and noisy-OR networks. The bounds determine confidence intervals for the desired likelihoods and become useful when the size of the network (or clique size) precludes exact computations. We illustrate the tightness of the obtained bounds by numerical experiments.

Activity Zones for Context-Aware Computing

Location is a primary cue in many context-aware computing systems, and is often represented as a global coordinate, room number, or Euclidean distance various landmarks. A user?s concept of location, however, is often defined in terms of regions in which common activities occur. We show how to partition a space into such regions based on patterns of observed user location and motion. These regions, which we call activity zones, represent regions of similar user activity, and can be used to trigger application actions, retrieve information based on previous context, and present information to users. We suggest that context-aware applications can benefit from a location representation learned from observing users. We describe an implementation of our system and present two example applications whose behavior is controlled by users? entry, exit, and presence in the zones.

Delegation, Arbitration and High-Level Service Discovery as Key Elements of a Software Infrastructure for Pervasive Computing

The dream of pervasive computing is slowly becoming a reality. A number of projects around the world are constantly contributing ideas and solutions that are bound to change the way we interact with our environments and with one another. An essential component of the future is a software infrastructure that is capable of supporting interactions on scales ranging from a single physical space to intercontinental collaborations. Such infrastructure must help applications adapt to very diverse environments and must protect people's privacy and respect their personal preferences. In this paper we indicate a number of limitations present in the software infrastructures proposed so far (including our previous work). We then describe the framework for building an infrastructure that satisfies the abovementioned criteria. This framework hinges on the concepts of delegation, arbitration and high-level service discovery. Components of our own implementation of such an infrastructure are presented.

Computing 3-D Motion in Custom Analog and Digital VLSI

This thesis examines a complete design framework for a real-time, autonomous system with specialized VLSI hardware for computing 3-D camera motion. In the proposed architecture, the first step is to determine point correspondences between two images. Two processors, a CCD array edge detector and a mixed analog/digital binary block correlator, are proposed for this task. The report is divided into three parts. Part I covers the algorithmic analysis; part II describes the design and test of a 32$\time $32 CCD edge detector fabricated through MOSIS; and part III compares the design of the mixed analog/digital correlator to a fully digital implementation.

Using Special-Purpose Computing to Examine Chaotic Behavior in Nonlinear Mappings

Studying chaotic behavior in nonlinear systems requires numerous computations in order to simulate the behavior of such systems. The Standard Map Machine was designed and implemented as a special computer for performing these intensive computations with high-speed and high-precision. Its impressive performance is due to its simple architecture specialized to the numerical computations required of nonlinear systems. This report discusses the design and implementation of the Standard Map Machine and its use in the study of nonlinear mappings; in particular, the study of the standard map.

Cloud Computing - health care's silver lining.

Cloud computing is the technology prescription that will help the UK’s National Health Service (NHS) beat the budget constraints imposed as a consequence of the credit crunch. The internet based shared data and services resource will revolutionise the management of medical records and patient information while saving the NHS millions of pounds.

Encouraging Complementary Fuzzy Rules within Iterative Rule Learning

M. Galea, Q. Shen and V. Singh. Encouraging Complementary Fuzzy Rules within Iterative Rule Learning. Proceedings of the 2005 UK Workshop on Computational Intelligence, pages 15-22.

Saying isn't necessarily believing: influencing self-theories in computing

Simon, B., Hanks, B., Murphy, L., Fitzgerald, S., McCauley, R., Thomas, L., and Zander, C. 2008. Saying isn't necessarily believing: influencing self-theories in computing. In Proceeding of the Fourth international Workshop on Computing Education Research (Sydney, Australia, September 06 - 07, 2008). ICER '08. ACM, New York, NY, 173-184.

From Limen to Lumen: computing students in liminal spaces.From Limen to Lumen: computing students in liminal spaces

Eckerdal, A., McCartney, R., Mostr?m, J. E., Sanders, K., Thomas, L., and Zander, C. 2007. From Limen to Lumen: computing students in liminal spaces. In Proceedings of the Third international Workshop on Computing Education Research (Atlanta, Georgia, USA, September 15 - 16, 2007). ICER '07. ACM, New York, NY, 123-132.

‘Complementary & alternative medicine’ (CAM): ethical and policy issues

Editorial for Bioethics 2016. 30:(2)

Mermera: Non-Coherent Distributed Shared Memory for Parallel Computing

The proliferation of inexpensive workstations and networks has prompted several researchers to use such distributed systems for parallel computing. Attempts have been made to offer a shared-memory programming model on such distributed memory computers. Most systems provide a shared-memory that is coherent in that all processes that use it agree on the order of all memory events. This dissertation explores the possibility of a significant improvement in the performance of some applications when they use non-coherent memory. First, a new formal model to describe existing non-coherent memories is developed. I use this model to prove that certain problems can be solved using asynchronous iterative algorithms on shared-memory in which the coherence constraints are substantially relaxed. In the course of the development of the model I discovered a new type of non-coherent behavior called Local Consistency. Second, a programming model, Mermera, is proposed. It provides programmers with a choice of hierarchically related non-coherent behaviors along with one coherent behavior. Thus, one can trade-off the ease of programming with coherent memory for improved performance with non-coherent memory. As an example, I present a program to solve a linear system of equations using an asynchronous iterative algorithm. This program uses all the behaviors offered by Mermera. Third, I describe the implementation of Mermera on a BBN Butterfly TC2000 and on a network of workstations. The performance of a version of the equation solving program that uses all the behaviors of Mermera is compared with that of a version that uses coherent behavior only. For a system of 1000 equations the former exhibits at least a 5-fold improvement in convergence time over the latter. The version using coherent behavior only does not benefit from employing more than one workstation to solve the problem while the program using non-coherent behavior continues to achieve improved performance as the number of workstations is increased from 1 to 6. This measurement corroborates our belief that non-coherent shared memory can be a performance boon for some applications.

Distributed Parallel Computing in Mermera: Mixing Noncoherent Shared Memories

Programmers of parallel processes that communicate through shared globally distributed data structures (DDS) face a difficult choice. Either they must explicitly program DDS management, by partitioning or replicating it over multiple distributed memory modules, or be content with a high latency coherent (sequentially consistent) memory abstraction that hides the DDS' distribution. We present Mermera, a new formalism and system that enable a smooth spectrum of noncoherent shared memory behaviors to coexist between the above two extremes. Our approach allows us to define known noncoherent memories in a new simple way, to identify new memory behaviors, and to characterize generic mixed-behavior computations. The latter are useful for programming using multiple behaviors that complement each others' advantages. On the practical side, we show that the large class of programs that use asynchronous iterative methods (AIM) can run correctly on slow memory, one of the weakest, and hence most efficient and fault-tolerant, noncoherence conditions. An example AIM program to solve linear equations, is developed to illustrate: (1) the need for concurrently mixing memory behaviors, and, (2) the performance gains attainable via noncoherence. Other program classes tolerate weak memory consistency by synchronizing in such a way as to yield executions indistinguishable from coherent ones. AIM computations on noncoherent memory yield noncoherent, yet correct, computations. We report performance data that exemplifies the potential benefits of noncoherence, in terms of raw memory performance, as well as application speed.

Open Issues on TCP for Mobile Computing

We discuss the design principles of TCP within the context of heterogeneous wired/wireless networks and mobile networking. We identify three shortcomings in TCP's behavior: (i) the protocol's error detection mechanism, which does not distinguish different types of errors and thus does not suffice for heterogeneous wired/wireless environments, (ii) the error recovery, which is not responsive to the distinctive characteristics of wireless networks such as transient or burst errors due to handoffs and fading channels, and (iii) the protocol strategy, which does not control the tradeoff between performance measures such as goodput and energy consumption, and often entails a wasteful effort of retransmission and energy expenditure. We discuss a solution-framework based on selected research proposals and the associated evaluation criteria for the suggested modifications. We highlight an important angle that did not attract the required attention so far: the need for new performance metrics, appropriate for evaluating the impact of protocol strategies on battery-powered devices.

Computing a Uniform Scaling Parameter for 3D Registration of Lung Surfaces

A difficulty in lung image registration is accounting for changes in the size of the lungs due to inspiration. We propose two methods for computing a uniform scale parameter for use in lung image registration that account for size change. A scaled rigid-body transformation allows analysis of corresponding lung CT scans taken at different times and can serve as a good low-order transformation to initialize non-rigid registration approaches. Two different features are used to compute the scale parameter. The first method uses lung surfaces. The second uses lung volumes. Both approaches are computationally inexpensive and improve the alignment of lung images over rigid registration. The two methods produce different scale parameters and may highlight different functional information about the lungs.

A Customizable Camera-based Human Computer Interaction System Allowing People With Disabilities Autonomous Hands Free Navigation of Multiple Computing Task

Many people suffer from conditions that lead to deterioration of motor control and makes access to the computer using traditional input devices difficult. In particular, they may loose control of hand movement to the extent that the standard mouse cannot be used as a pointing device. Most current alternatives use markers or specialized hardware to track and translate a user's movement to pointer movement. These approaches may be perceived as intrusive, for example, wearable devices. Camera-based assistive systems that use visual tracking of features on the user's body often require cumbersome manual adjustment. This paper introduces an enhanced computer vision based strategy where features, for example on a user's face, viewed through an inexpensive USB camera, are tracked and translated to pointer movement. The main contributions of this paper are (1) enhancing a video based interface with a mechanism for mapping feature movement to pointer movement, which allows users to navigate to all areas of the screen even with very limited physical movement, and (2) providing a customizable, hierarchical navigation framework for human computer interaction (HCI). This framework provides effective use of the vision-based interface system for accessing multiple applications in an autonomous setting. Experiments with several users show the effectiveness of the mapping strategy and its usage within the application framework as a practical tool for desktop users with disabilities.