No standard method is available for detecting protozoan parasites on foods such as soft fruit and salad vegetables. We report on optimizing methods for detecting Cryptosporidium parvum on lettuce and raspberries. These methods are based on four basic stages: extraction of oocysts from the foodstuffs, concentration of the extract and separation of the oocysts from food materials, staining of the...

When choosing parameters for a tactile action, it is useful to be able to choose parameters that will optimize the discriminating power of the tactile data acquired during the action. We propose a way to extract this information about informative grasp parameters from a deep network trained to perform a classification task on the tactile data. We do this by defining a new cost function on the n...

The image segmentation methods based on Markovian assumption consist in optimizing a Gibbs energy function which depends on the observation field and the segmented field. This energy function can be represented as a sum of potentials defined on cliques which are subsets of the grid of sites. The Potts model is the most commonly used to represent the segmented field. However, this model expresse...

Scale Invariant Feature Transform (SIFT) algorithm is a widely used computer vision algorithm that detects and extracts local feature descriptors from images. SIFT is computationally intensive, making it infeasible for single threaded implementation to extract local feature descriptors for high-resolution images in real time. In this paper, an approach to parallelization of the SIFT algorithm i...

The need for efficient transport management based applications has witnessed a tremendous growth due to the explosive burst in population and the corresponding demand for transport services. In this paper we propose a novel Mass Transit Routing 406 Daning Chen et al. and Optimization Tool (MTRO), which uses Data Mining (DM) techniques to extract information from the commuter database and assist...

Modern data flows generalize traditional Extract-TransformLoad and data integration workflows in order to enable end-to-end data processing and analytics. The more complex they become, the more pressing the need for automated optimization solutions. Optimizing data flows comes in several forms, among which, optimal task ordering is one of the most challenging ones. We take a practical approach;...

Non-invasive approaches to assess tissue function could improve significantly current methods to diagnose diseases and optimize engineered tissues. In this study, we describe a two-photon excited fluorescence microscopy approach that relies entirely on endogenous fluorophores to dynamically quantify functional metabolic readouts from individual cells within three-dimensional engineered tissues ...

Application scenarios such as legacy data migration, Extract-TransformLoad (ETL) processes, and data cleaning require the transformation of input tuples into output tuples. Traditional approaches for implementing these data transformations enclose solutions as Persistent Stored Modules (PSM) executed by an RDBMS or transformation code using a commercial ETL tool. Neither of these is easily main...

Knowledge of the routes frequently used by the tracked objects are embedded in the massive trajectory databases archiving spatialtemporal movement data of the objects in question. Such knowledge has various applications in optimizing ports’ operations, understanding wild-life behaviours, and navigation/route-recommendation systems but is difficult to extract in many real-life scenarios, where t...

Phrase alignment is a crucial step in phrase-based statistical machine translation. We explore a way of improving phrase alignment by adding syntactic information in the form of chunks as soft constraints guided by an in-depth and detailed analysis on a hand-aligned data set. We extend a probabilistic phrase alignment model that extracts phrase pairs by optimizing phrase pair boundaries over th...