In this paper we present a new approach to plan understanding that explains observed actions in terms of domain knowledge. The process operates over hierarchical methods and utilizes an incremental form of data-driven abductive inference. We report experiments on problems from the Monroe corpus that demonstrate a basic ability to construct plausible explanations, graceful degradation of perform...

Online job scheduling has demonstrated to be a key factor impacting the output performance of batch processing systems. Existing researches either proposed solutions to a single-machine processing system, or focused on minimizing the total job completion time for multiple-machine batch processing systems. Yet the study on the approaches with the objective of minimizing the job delay time on a p...

Retaining workers on micro-task crowdsourcing platforms is essential in order to guarantee the timely completion of batches of Human Intelligence Tasks (HITs). Worker retention is also a necessary condition for the introduction of SLAs on crowdsourcing platforms. In this paper, we introduce novel pricing schemes aimed at improving the retention rate of workers working on long batches of similar...

These days the use of models to predict process behaviour has become more and more common. The main reasons for this are that it is more practical and economical than using for example the trial and error method with expensive equipment. In the field of preparative chromatography the use of models to predict process behaviour has been proven to be very useful, especially for batch chromatograph...

With supervisory control theory it is possible to describe controllers which influence the behaviour of a system by disabling controllable events. But sometimes it is desirable to have a controller which not only disables controllable events but also chooses one among the enabled ones. This event can be interpreted as a command given to the plant. This idea is formalized in the concept of an im...

Traditional high performance computing (HPC)/ supercomputing, analytics and mainstream realtime/batch computing are quickly converging. Mainstream workloads are crossing over the high performance computing arena, demanding faster analytics/batching, resource-intensive computations and algorithms. To succeed in today’s accelerating digital world, enterprises must collect and analyze mind-bogglin...

We present improvements to the index-calculus algorithm for the computation of the ideal class group and regulator of a real quadratic field. Our improvements consist of applying the double large prime strategy, an improved structured Gaussian elimination strategy, and the use of Bernstein’s batch smoothness algorithm. We achieve a significant speed-up and are able to compute the ideal class gr...

We present the first fair e-cash system with a compact wallet that enables users to spend efficiently k coins while only sending to the merchant O(λ log k) bits, where λ is a security parameter. The best previously known schemes require to transmit data of size at least linear in the number of spent coins. This result is achieved thanks to a new way to use the Batch RSA technique and a tree-bas...

This application note outlines the methodology implemented in the NextBio platform (Figure 1) for detecting changes in DNA methylation for data produced on the Illumina Infinium methylation assays. The method analyzes data in a patient-centric context, i.e., data are obtained for an individual patient, rather than as a batch. Therefore, the underlying analysis must be expanded to handle this co...

A lot of practical machine learning applications deal with interactive classification problems where trained classifiers are used to help humans find positive examples that are of interest to them. Typically, these classifiers label a large number of test examples and present the humans with a ranked list to review. The humans involved in this process are often expensive domain experts with lim...