Improving Spatial Codification in Semantic Segmentation

This paper explores novel approaches for improving the spatial codification for the pooling of local descriptors to solve the semantic segmentation problem. We propose to partition the image into three regions for each object to be described: Figure, Border and Ground. This partition aims at minimizing the influence of the image context on the object description and vice versa by introducing an intermediate zone around the object contour. Furthermore, we also propose a richer visual descriptor of the object by applying a Spatial Pyramid over the Figure region. Two novel Spatial Pyramid configurations are explored: Cartesian-based and crown-based Spatial Pyramids. We test these approaches with state-of-the-art techniques and show that they improve the Figure-Ground based pooling in the Pascal VOC 2011 and 2012 semantic segmentation challenges.Comment: Paper accepted at the IEEE International Conference on Image Processing, ICIP 2015. Quebec City, 27-30 September. Project page: https://imatge.upc.edu/web/publications/improving-spatial-codification-semantic-segmentatio

Real road networks on digital maps with applications in the search for optimal routes

Google Maps web mapping service allows, through its extensive API development tool, to extract, process and store updated and real-time road information such as the aerial view of a road network, the travel time and distance between two points and the geographic coordinates of intersections (Di Natale et al. in understanding and using the controller area network communication protocol. Springer, New York, NY, 2012 [1]). However, trivial data required in the construction of the digraph, such as the relationship of the streets associated to those intersections and the type of direction that corresponds to each street, do not exist as an attribute in the API since they are not freely accessible or an excessive cost must be paid for the database. Therefore, a practical way to obtain this specific information is through the development of an application that allows the visual selection of the characteristic elements of a network and the extraction of the necessary data in the construction of related digraphs as a tool in the solution of road problems (Rutty et al. in Transp Res Part Transp Environ 24:44–51, 2013 [2]). This research proposes a method to build digraphs with an application in the Google Maps API in the visual extraction of elements such as vertices (intersections), edges (streets) and direction arrows (road direction), allowing the application of Dijkstra’s algorithm in search of alternative routes

Development and Evaluation of Management Information Systems for Christian Workers Movement Multi-Purpose Cooperative

The Christian Workers Movement Multi-Purpose Cooperative (CWMMC) is a financial institution that caters to more than a thousand members in rendering timely financial assistance by making use of manual transaction processing. The company has encountered a number of problems pertaining to its services, strategic office location, and data / information management. This study was conducted in an attempt to design and develop a software system that would make loaning processes and other company-related business transactions simple, convenient, reliable, and dependable. A management information system was developed for and implemented at CWMMC. The software was found acceptable to the end-users and technical experts. Hence, it was recommended that the software be used continuously

Propuesta de un sistema de comunicación para interconectar las sedes, INSFOP y UNICAM en los departamentos de Esteli y Madrid respectivamente.

El presente documento tiene como objeto brindar una propuesta de diseño de un sistema de comunicación que permita interconectar 2 sede de la Institución INSFOP (Instituto de Formación Permanente) en Estelí, con una sede afiliada llamada UNICAM(Universidad Campesina) en Somoto, Madrid, con el fin de brindar servicio de voz, video y datos en general

Insight Centre for Data Analytics (DCU) at TRECVid 2014: instance search and semantic indexing tasks

Insight-DCU participated in the instance search (INS) and semantic indexing (SIN) tasks in 2014. Two very different approaches were submitted for instance search, one based on features extracted using pre-trained deep convolutional neural networks (CNNs), and another based on local SIFT features, large vocabulary visual bag-of-words aggregation, inverted index-based lookup, and geometric verification on the top-N retrieved results. Two interactive runs and two automatic runs were submitted, the best interactive runs achieved a mAP of 0.135 and the best automatic 0.12. Our semantic indexing runs were based also on using convolutional neural network features, and on Support Vector Machine classifiers with linear and RBF kernels. One run was submitted to the main task, two to the no annotation task, and one to the progress task. Data for the no-annotation task was gathered from Google Images and ImageNet. The main task run has achieved a mAP of 0.086, the best no-annotation runs had a close performance to the main run by achieving a mAP of 0.080, while the progress run had 0.043

Análisis comparativo de la reglamentación pertinente de centros educativos. Casos de estudio pabellón a (ingeniería) y pabellón o (industrial)

En el presente trabajo se tiene objetivo principal comparar las normas de arquitectura y ver el nivel de importancia en los pabellones de estudio. Para lograr este objetivo, la investigación se desarrolló mediante la lectura de reglamentos nacionales e internacionales, la normativa de MINEDU, libros y artículos del tema, luego se comparó y verificó las características particulares de cada pabellón, en el análisis de los resultados obtenidos de normas internacionales hay un consenso en bienestar de los alumnos con respecto al ambiente de estudio, también el cumplimiento del reglamento y normas del MINEDU en las infraestructuras. En el trabajo de investigación también se vio el tema de arquitectura bioclimática en centros educativos, donde se comprueba la influencia en el diseño de los pabellones

BEEHOPE: um projeto de conservação das subespécies nativas de abelha da Europa Ocidental (linhagem M) à escala Europeia

O projeto BEEHOPE, com o título original “Honeybee conservation centres in western Europe - an innovative strategy using sustainable beekeeping to reduce honeybee decline”, foi um dos 10 aprovados na área da biodiversidade do 5º concurso transnacional (2013-2014) BiodivErsA/FACCE-JPI (http://www.biodiversa.org/766), subordinado ao tema “Promover sinergias e reduzir o compromisso entre o abastecimento de alimentos, biodiversidade e serviços dos ecossistemas”. A diversidade nativa das populações de abelha melífera (Apis mellifera) da linhagem da Europa ocidental (M) tem vindo a ser crescentemente ameaçada pela introdução massiva de colónias da linhagem da Europa oriental (C, onde se incluem as subespécies A. m. ligustica, A. m. carnica, A. m. macedónica etc.), e também por outros fatores bióticos (Varroa e vírus associados, Nosema etc.) e abióticos (pesticidas, perda e fragmentação de habitat, alterações climáticas etc.). É neste contexto que surge o projeto BEEHOPE, o qual tem por objetivo último contribuir para a conservação da diversidade genética das populações de abelha melífera da linhagem M.info:eu-repo/semantics/publishedVersio

Risk factor screening to identify women requiring oral glucose tolerance testing to diagnose gestational diabetes : a systematic review and meta-analysis and analysis of two pregnancy cohorts

BACKGROUND: Easily identifiable risk factors including: obesity and ethnicity at high risk of diabetes are commonly used to indicate which women should be offered the oral glucose tolerance test (OGTT) to diagnose gestational diabetes (GDM). Evidence regarding these risk factors is limited however. We conducted a systematic review (SR) and meta-analysis and individual participant data (IPD) analysis to evaluate the performance of risk factors in identifying women with GDM. METHODS: We searched MEDLINE, Medline in Process, Embase, Maternity and Infant Care and the Cochrane Central Register of Controlled Trials (CENTRAL) up to August 2016 and conducted additional reference checking. We included observational, cohort, case-control and cross-sectional studies reporting the performance characteristics of risk factors used to identify women at high risk of GDM. We had access to IPD from the Born in Bradford and Atlantic Diabetes in Pregnancy cohorts, all pregnant women in the two cohorts with data on risk factors and OGTT results were included. RESULTS: Twenty nine published studies with 211,698 women for the SR and a further 14,103 women from two birth cohorts (Born in Bradford and the Atlantic Diabetes in Pregnancy study) for the IPD analysis were included. Six studies assessed the screening performance of guidelines; six examined combinations of risk factors; eight evaluated the number of risk factors and nine examined prediction models or scores. Meta-analysis using data from published studies suggests that irrespective of the method used, risk factors do not identify women with GDM well. Using IPD and combining risk factors to produce the highest sensitivities, results in low specificities (and so higher false positives). Strategies that use the risk factors of age (>25 or >30) and BMI (>25 or 30) perform as well as other strategies with additional risk factors included. CONCLUSIONS: Risk factor screening methods are poor predictors of which pregnant women will be diagnosed with GDM. A simple approach of offering an OGTT to women 25 years or older and/or with a BMI of 25kg/m2 or more is as good as more complex risk prediction models. Research to identify more accurate (bio)markers is needed. Systematic Review Registration: PROSPERO CRD42013004608