Desire lines in big data : using event data for process discovery and conformance checking

Recently, the Task Force on Process Mining released the Process Mining Manifesto. The manifesto is supported by 53 organizations and 77 process mining experts contributed to it. The active contributions from end-users, tool vendors, consultants, analysts, and researchers illustrate the growing relevance of process mining as a bridge between data mining and business process modeling. This paper summarizes the manifesto and explains why process mining is a highly relevant, but also very challenging, research area. This way we hope to stimulate the broader IS (Information Systems) and KM (Knowledge Management) communities to look at process-centric knowledge discovery. This paper summarizes the manifesto and is based on a paper with the same title that appeared in the December 2011 issue of SIGKDD Explorations (Volume 13, Issue 2)

The property finance business in South Africa

Problem Statement: The business of property finance has not been properly documented in South Africa. Available resource material focuses on the perspective of the property developer and investor largely neglecting the business of property finance. Thus comprehensive information on this business was not available to students and researchers This study set out to correct this deficiency. Research Procedure: Key property finance personnel in the major banks in the Republic of South Africa were interviewed to establish how the business of property finance is conducted. Jointly the interviewees represent 77% by volume of business over a period of two years A parallel process of literature research was undertaken to compliment the interview research and provide technical depth to the findings. Findings: The empirical and literature research results were combined to comprehensively document the processes, structures, systems, productsBusiness ManagementM. Com. (Business Management

Colloidal swarms can settle faster than isolated particles

Colloid sedimentation has played a seminal role in the development of statistical physics thanks to the celebrated experiments by Perrin, which gave a concrete demonstration of molecular reality. Recently, the investigation of sedimentation equilibrium has provided valuable information on a wide class of systems, ranging from simple colloids to active particles and biological fluids [1]. Yet, many aspects of the sedimentation kinetics deserve to be further investigated. Here we present some rather surprising results concerning the effect of interactions on particle settling [2]. Usually, the settling velocity of a colloidal suspension decreases with concentration: this well-known effect is called “hindered’’ settling. By experimenting on model colloids in which depletion forces can carefully be tuned, we conversely show that attractive interactions consistently “promote particle settling, so much that, close to a phase-separation line, the sedimentation velocity of a moderately concentrated dispersion can even exceed its single-particle value. At larger particle volume fraction , however, hydrodynamic hindrance eventually takes over. Hence, v() actually displays a non-monotonic trend that may threaten the stability of the settling front to thermal perturbations. By discussing a representative case, we show that these results are relevant to the investigation of protein weak association effects by ultracentrifugation. References. [1] R. Piazza, Reports of Progress in Physics, 2014, 77, 056602. [2] E. Lattuada, S. Buzzaccaro, R. Piazza, Phys. Rev. Lett. 2016, 116, 03830

Results of Environmental Scanning Applied to the Design of a Deer Management Decision Support System (DSS) For The United States and California

Using freely available internet search tools for environmental scanning, information related to deer management was collected, categorized, and evaluated with the goal of providing public decision support. Key issues raised in the public debate discovered by the search are addressed with relevant information formatted as output for a decision support system – dashboard elements. A graph addresses contradictory reports about the current direction of the deer population; the trend since 2006 appears to be down. Another graph illustrates the approximate longterm population trend; the current U.S. white-tailed deer population is about the same as in 1500. A table summarizes profiles of state deer issues and strategies. Only eleven states are trying to reduce their deer population. A graph illustrates the rise and fall of the California population, the most dramatic population decline in the U.S. over the past 100 years. Hunting pressure and herd demographic management are found to be related to the decline, making these candidate variables for attention in the decision support system. This case application is designed to illustrate methods the author has learned in creating a variety of decision support applications for technology companies

Route Planning in Transportation Networks

We survey recent advances in algorithms for route planning in transportation networks. For road networks, we show that one can compute driving directions in milliseconds or less even at continental scale. A variety of techniques provide different trade-offs between preprocessing effort, space requirements, and query time. Some algorithms can answer queries in a fraction of a microsecond, while others can deal efficiently with real-time traffic. Journey planning on public transportation systems, although conceptually similar, is a significantly harder problem due to its inherent time-dependent and multicriteria nature. Although exact algorithms are fast enough for interactive queries on metropolitan transit systems, dealing with continent-sized instances requires simplifications or heavy preprocessing. The multimodal route planning problem, which seeks journeys combining schedule-based transportation (buses, trains) with unrestricted modes (walking, driving), is even harder, relying on approximate solutions even for metropolitan inputs.Comment: This is an updated version of the technical report MSR-TR-2014-4, previously published by Microsoft Research. This work was mostly done while the authors Daniel Delling, Andrew Goldberg, and Renato F. Werneck were at Microsoft Research Silicon Valle

Predictive biometrics: A review and analysis of predicting personal characteristics from biometric data

Interest in the exploitation of soft biometrics information has continued to develop over the last decade or so. In comparison with traditional biometrics, which focuses principally on person identification, the idea of soft biometrics processing is to study the utilisation of more general information regarding a system user, which is not necessarily unique. There are increasing indications that this type of data will have great value in providing complementary information for user authentication. However, the authors have also seen a growing interest in broadening the predictive capabilities of biometric data, encompassing both easily definable characteristics such as subject age and, most recently, `higher level' characteristics such as emotional or mental states. This study will present a selective review of the predictive capabilities, in the widest sense, of biometric data processing, providing an analysis of the key issues still adequately to be addressed if this concept of predictive biometrics is to be fully exploited in the future