Local matching indicators for transport problems with concave costs

In this paper, we introduce a class of indicators that enable to compute efficiently optimal transport plans associated to arbitrary distributions of N demands and M supplies in R in the case where the cost function is concave. The computational cost of these indicators is small and independent of N. A hierarchical use of them enables to obtain an efficient algorithm

Determination of Freeze-out Conditions from Lattice QCD Calculations

Freeze-out conditions in Heavy Ion Collisions are generally determined by comparing experimental results for ratios of particle yields with theoretical predictions based on applications of the Hadron Resonance Gas model. We discuss here how this model dependent determination of freeze-out parameters may eventually be replaced by theoretical predictions based on equilibrium QCD thermodynamics.Comment: presented at the International Conference "Critical Point and Onset of Deconfinement - CPOD 2011", Wuhan, November 7-11, 201

Running a Production Grid Site at the London e-Science Centre

This paper describes how the London e-Science Centre cluster MARS, a production 400+ Opteron CPU cluster, was integrated into the production Large Hadron Collider Compute Grid. It describes the practical issues that we encountered when deploying and maintaining this system, and details the techniques that were applied to resolve them. Finally, we provide a set of recommendations based on our experiences for grid software development in general that we believe would make the technology more accessible. © 2006 IEEE

A Data Quality Framework for Process Mining of Electronic Health Record Data

Reliable research demands data of known quality. This can be very challenging for electronic health record (EHR) based research where data quality issues can be complex and often unknown. Emerging technologies such as process mining can reveal insights into how to improve care pathways but only if technological advances are matched by strategies and methods to improve data quality. The aim of this work was to develop a care pathway data quality framework (CP-DQF) to identify, manage and mitigate EHR data quality in the context of process mining, using dental EHRs as an example. Objectives: To: 1) Design a framework implementable within our e-health record research environments; 2) Scale it to further dimensions and sources; 3) Run code to mark the data; 4) Mitigate issues and provide an audit trail. Methods: We reviewed the existing literature covering data quality frameworks for process mining and for data mining of EHRs and constructed a unified data quality framework that met the requirements of both. We applied the framework to a practical case study mining primary care dental pathways from an EHR covering 41 dental clinics and 231,760 patients in the Republic of Ireland. Results: Applying the framework helped identify many potential data quality issues and mark-up every data point affected. This enabled systematic assessment of the data quality issues relevant to mining care pathways. Conclusion: The complexity of data quality in an EHR-data research environment was addressed through a re-usable and comprehensible framework that met the needs of our case study. This structured approach saved time and brought rigor to the management and mitigation of data quality issues. The resulting metadata is being used within cohort selection, experiment and process mining software so that our research with this data is based on data of known quality. Our framework is a useful starting point for process mining researchers to address EHR data quality concerns

STATS - A Point Access Method for Multidimensional Clusters.

The ubiquity of high-dimensional data in machine learning and data mining applications makes its efficient indexing and retrieval from main memory crucial. Frequently, these machine learning algorithms need to query specific characteristics of single multidimensional points. For example, given a clustered dataset, the cluster membership (CM) query retrieves the cluster to which an object belongs. To efficiently answer this type of query we have developed STATS, a novel main-memory index which scales to answer CM queries on increasingly big datasets. Current indexing methods are oblivious to the structure of clusters in the data, and we thus, develop STATS around the key insight that exploiting the cluster information when indexing and preserving it in the index will accelerate look up. We show experimentally that STATS outperforms known methods in regards to retrieval time and scales well with dataset size for any number of dimensions

Water Vapour Content of the Atmosphere in Relation to Surface Humidity

The theoretical relationship between precipitate water vapour in the atmosphere & surface humidity has been investigated. By introducing the concept of a lapse parameter alpha, a method has been devised for estimation of precipitable water vapour. Results have been compared for six Indian Stations for which upper air data were available

Maximizing Maximal Angles for Plane Straight-Line Graphs

Let $G=(S, E)$ be a plane straight-line graph on a finite point set $S\subset\R^2$ in general position. The incident angles of a vertex $p \in S$ of $G$ are the angles between any two edges of $G$ that appear consecutively in the circular order of the edges incident to $p$. A plane straight-line graph is called $\phi$-open if each vertex has an incident angle of size at least $\phi$. In this paper we study the following type of question: What is the maximum angle $\phi$ such that for any finite set $S\subset\R^2$ of points in general position we can find a graph from a certain class of graphs on $S$ that is $\phi$-open? In particular, we consider the classes of triangulations, spanning trees, and paths on $S$ and give tight bounds in most cases.Comment: 15 pages, 14 figures. Apart of minor corrections, some proofs that were omitted in the previous version are now include