No abstract

The problem considered is to locate a point in a given convex polyhedron which maximizes the minimum Euclidean distance from a given set of points. The paper describes several possible application areas and shows the existence of a finite set of candidates for the optimal solution. A combinatorial algorithm is presented for the problem in three dimensions, and it is compared with existing nonconvex programming algorithms.

Massive open online courses (MOOCs) are a recent development in online education aimed at unlimited participation and open access via the Web. They are a potentially disruptive technology, changing how education is delivered and funded around the world. MOOCs are relevant to software researchers and practitioners, not only because they will increasingly receive lifelong education through MOOCs and related technologies, but also because content creation, delivery, and enhancement of MOOCs is evolving into a new form of socially-and cognitivelyembedded software development. This paper discusses how education is being enhanced by MOOCs and other digital learning technology. In particular, we distinguish the free educational content provided by MOOCs from the emerging collaborative processes through which MOOCs are created, which is arguably more transformative on education than the content itself. We discuss blended models of higher education to suit different learner communities, as well as nascent moves toward the creation of instructional communities of educators that transcend institutional boundaries. We also explore MOOCs and their evolution as a subject for research in the learning sciences and implications for R&D in software and systems engineering.

Abstract

The Event service is the earliest CORBA solution to the message queue model of communication in distributed systems. Typical implementations however suffer from the lack of event delivery guarantees. The loss of messages is aggravated in the presence of burstiness in the input to the Event service, and occurrences of isolated bursts of traffic could also have serious effects. In this paper we develop stochastic reward net (SRN) models that can aid in the study and conBguration of the Event service to conform to design specifications. To capture burstiness in the input, Markov modulated Poisson process (MMPP) is used as the input source. Erlang distributed event consumption times are used in the models to accommodate more general distributions and a wider range of variances. The models also take into con:iideration the FIFO discard policy adopted in many Event service implementations. The SRN models are solved using [he tool SPNI? The applicability of the models to the CORBA Notification service is also briefly discussed.