Dynamic Pipeline: an adaptive solution for big data

The Dynamic Pipelineis a concurrent programming pattern amenable to be parallelized. Furthermore, the number of processing units used in the parallelization is adjusted to the size of the problem, and each processing unit uses a reduced memory footprint. Contrary to other approaches, the Dynamic Pipeline can be seen as ageneralization of the (parallel) Divide and Conquer schema, where systems can be reconfigured depending on the particular instance of the problem to be solved. We claim that the Dynamic Pipelines is useful to deal with Big Data related problems. In particular, we have designed and implemented algorithms for computing graphs parameters as number of triangles, connected components, and maximal cliques, among others. Currently, we are focused on designing and implementing an efficient algorithm to evaluate conjunctive query.Peer ReviewedPostprint (author's final draft

Visualization of back pain data-A 3-D solution

Traditional approaches to gathering and visualizing pain data rely on two-dimensional (2-D) human body models, where different types of sensation are recorded with various monochrome symbols. We proposean alternative that uses a three-dimensional (3-D) representation of the human body, which can be marked in color to visualize and record pain data

The GIS and data solution for advanced business analysis

The GIS Business Analyst is a suite of Geographic Information System (GIS)-enabled tools, wizards, and data that provides business professionals with a complete solution for site evaluation, selective customer profiling, and trade area market analysis. Running simple reports, mapping the results, and performing complex probability models are among the capabilities The GIS Business Analyst offers in one affordable desktop analysis solution. Data and analyses produced by The GIS Business Analyst can be shared across departments, reducing redundant research and marketing efforts, speeding analysis of results, and increasing employee efficiency. The GIS Business Analyst is the first suite of tools for unlocking the intelligence of geography, demographic, consumer lifestyle, and business data. It is a valuable asset for business decision making such as analyzing market share and competition, determining new site expansions or reductions, and targeting new customers. The ability to analyze and visualize the geographic component of business data reveals trends, patterns, and opportunities hidden in tabular data. By combining information, such as sales data of the organization, customer information, and competitor locations, with geographic data, such as demographics, territories, or store locations, the GIS Business Analyst helps the user better understand organization market, organization customers, and organization competition. The business intelligence systems bring geographic information systems, marketing analysis tools, and demographic data products together to offer the user powerful ways to compete in today's business strategies.Geographical Informatic Systems, business analysis

Recording of time-varying back-pain data: A wireless solution

Chronic back pain is a debilitating experience for a considerable proportion of the adult population, with a significant impact on countries’ economies and health systems. While there has been increasing anecdotal evidence to support the fact that for certain categories of patients (such as wheelchair users), the back pain experienced is dynamically varying with time, there is a relative scarcity of data to support and document this observation, with consequential impact upon such patients’ treatment and care. Part of the reason behind this state of affairs is the relative difficulty in gathering pain measurements at precisely defined moments in time. In this paper,we describe a wireless-enabled solution that collects both questionnaire and diagrammatic, visual-based data, via a pain drawing, which overcomes such limitations, enabling seamless data collection and its upload to a hospital server using existing wireless fidelity technology. Results show that it is generally perceived to be an easy-to-use and convenient solution to the challenges of anywhere/anytime data collection

Is the LMA solar-neutrino solution ruled out by SN1987A data?

The development of new supernova neutrino detectors relies on the expected hard energy spectrum of the nu_mu and nu_tau emitted in the supernova. We show that SN1987A was sensitive to the large mixing angle (LMA) and "just so" solution to the solar neutrino problem. We review the previous analysis of the SN1987A data and propose a new analysis. The results of this analysis strongly disfavor the LMA solution, provided the nu_mu and nu_tau are hard as predictedComment: 4 pages; 6 figures. Presented at the Europhysics Neutrino Oscillation Workshop, NOW 2000 (EPS, Lecce, Italy, Sept. 9-16, 2000) and to be published in Nucl. Phys. B (PS) (North Holland, Amsterdam, 2001