{"title":"Parallel spatial segmentation for the automated analysis of football","authors":"F. Siles, J. Saborío","doi":"10.1109/IWOBI.2015.7160140","DOIUrl":"https://doi.org/10.1109/IWOBI.2015.7160140","url":null,"abstract":"This work describes a computational methodology for the modelling and analysis of association football and its automatic interpretation. We describe several methods required to populate the modules of our purposed mathematical model, and provide empirical results of spatial segmentation on SD and HD videos in a multi-threaded, data-parallel computing environment.","PeriodicalId":373170,"journal":{"name":"2015 4th International Work Conference on Bioinspired Intelligence (IWOBI)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122693617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A new indicator for measurement of the quality of computational results based on statistical properties","authors":"Ricardo E. Monge, J. L. Crespo","doi":"10.1109/IWOBI.2015.7160146","DOIUrl":"https://doi.org/10.1109/IWOBI.2015.7160146","url":null,"abstract":"This paper explores different techniques which can be used to assess the quality of data resulting from computational processes and algorithms. The objective is to develop a numerical index of quality that would permit establishing a direct comparison between a variety of methods and computational techniques. A short summary of previous work is included, followed by the proposal (Section III) of the index of quality based on the interpretation of statistical properties and conditions. The fourth section is composed of a sample calculation of the Statistical Index of Quality, followed by the analysis of eight sample cases (Section V). This work is part of a broader study regarding the usage of bioinspired intelligence for the analysis of human DNA.","PeriodicalId":373170,"journal":{"name":"2015 4th International Work Conference on Bioinspired Intelligence (IWOBI)","volume":"170 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121539058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Cascante-Vindas, Francisco Siles, A. Díez, M. Andrés
{"title":"Optimization of micro-structured fiber optic devices for super-continuum generation","authors":"J. Cascante-Vindas, Francisco Siles, A. Díez, M. Andrés","doi":"10.1109/IWOBI.2015.7160167","DOIUrl":"https://doi.org/10.1109/IWOBI.2015.7160167","url":null,"abstract":"This study describes the optimized process for tapered fiber devices for an application in generating of super-continuum and a concrete example. These devices could prove very useful in bio-imaging applications. This process has been mentioned in many references, but without sufficient detail to allow other researchers can replicate in a simple and direct way. This article describes in detail the manufacturing process using a gas system in complete combustion.","PeriodicalId":373170,"journal":{"name":"2015 4th International Work Conference on Bioinspired Intelligence (IWOBI)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128867361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Serrato, Tetyana Baydyk, E. Kussul, A. Escalante-Estrada, Maria Teresa Gonzalez Rodriguez
{"title":"Recognition of pests on crops with a random subspace classifier","authors":"L. Serrato, Tetyana Baydyk, E. Kussul, A. Escalante-Estrada, Maria Teresa Gonzalez Rodriguez","doi":"10.1109/IWOBI.2015.7160138","DOIUrl":"https://doi.org/10.1109/IWOBI.2015.7160138","url":null,"abstract":"The purpose of this study is to develop and test a recognition system for the Colorado potato beetle. This task is very important for localizing the beetles and reducing the pesticide volume used to protect the harvest. We employ a beetle image dataset that contains 25 images representing different beetle positions and varying numbers of beetles. These images were collected from the Internet. Our recognition system is based on a special neural network, the random subspace classifier (RSC). We calculate the brightness, contrast, and contour orientation histograms of the images and use them as features and inputs to the RSC neural classifier. In addition, we describe the RSC structure and algorithms and analyse the obtained results. We obtained the best recognition rate of 85%.","PeriodicalId":373170,"journal":{"name":"2015 4th International Work Conference on Bioinspired Intelligence (IWOBI)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121142301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Discrimination between pathological voice categories using matching pursuit","authors":"A. Kumar, K. Daoudi","doi":"10.1109/IWOBI.2015.7160169","DOIUrl":"https://doi.org/10.1109/IWOBI.2015.7160169","url":null,"abstract":"There are several methods in the literature for pathological voice classification but there are very few methods which can classify pathological sub-groups. An attempt is made here to classify pathological sub-groups using matching pursuit decomposition method and is compared with PRAAT. Random forest classifier is used and frequency band of the atoms are used as feature. The result shows that we can classify adductor spasmodic dysphonia, keratosis and vocal nodules in a class of voices consisting of adductor spasmodic dysphonia, keratosis, paralysis, vocal nodules and vocal fold polyps with reasonably good classification accuracy. Both matching pursuit (MP) and PRAAT shows comparable classification scores but using MP is more advantageous over PRAAT since it doesn't rely on pitch information and extraction of pitch information in a pathological signal is a complex problem.","PeriodicalId":373170,"journal":{"name":"2015 4th International Work Conference on Bioinspired Intelligence (IWOBI)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115395357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. López de Ipiña, M. Iturrate, P. Calvo, B. Beitia, J. Garcia-Melero, A. Bergareche, P. de la Riva, J. Martí‐Massó, M. Faúndez-Zanuy, E. Sesa-Nogueras, J. Roure, Jordi Solé-Casals
{"title":"Selection of entropy based features for the analysis of the Archimedes' spiral applied to essential tremor","authors":"K. López de Ipiña, M. Iturrate, P. Calvo, B. Beitia, J. Garcia-Melero, A. Bergareche, P. de la Riva, J. Martí‐Massó, M. Faúndez-Zanuy, E. Sesa-Nogueras, J. Roure, Jordi Solé-Casals","doi":"10.1109/IWOBI.2015.7160160","DOIUrl":"https://doi.org/10.1109/IWOBI.2015.7160160","url":null,"abstract":"Biomedical systems are regulated by interacting mechanisms that operate across multiple spatial and temporal scales and produce biosignals with linear and non-linear information inside. In this sense entropy could provide a useful measure about disorder in the system, lack of information in time-series and/or irregularity of the signals. Essential tremor (ET) is the most common movement disorder, being 20 times more common than Parkinson's disease, and 50-70% of this disease cases are estimated to be genetic in origin. Archimedes spiral drawing is one of the most used standard tests for clinical diagnosis. This work, on selection of nonlinear biomarkers from drawings and handwriting, is part of a wide-ranging cross study for the diagnosis of essential tremor in BioDonostia Health Institute. Several entropy algorithms are used to generate nonlinear feayures. The automatic analysis system consists of several Machine Learning paradigms.","PeriodicalId":373170,"journal":{"name":"2015 4th International Work Conference on Bioinspired Intelligence (IWOBI)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116954805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Mekyska, Z. Galaz, Zdenek Mzourek, Z. Smékal, I. Rektorová, I. Eliasova, M. Kostalova, M. Mrackova, D. Berankova, M. Faúndez-Zanuy, K. L. D. Ipiña, J. B. Alonso
{"title":"Assessing progress of Parkinson's disease using acoustic analysis of phonation","authors":"J. Mekyska, Z. Galaz, Zdenek Mzourek, Z. Smékal, I. Rektorová, I. Eliasova, M. Kostalova, M. Mrackova, D. Berankova, M. Faúndez-Zanuy, K. L. D. Ipiña, J. B. Alonso","doi":"10.1109/IWOBI.2015.7160153","DOIUrl":"https://doi.org/10.1109/IWOBI.2015.7160153","url":null,"abstract":"This paper deals with a complex acoustic analysis of phonation in patients with Parkinson's disease (PD) with a special focus on estimation of disease progress that is described by 7 different clinical scales (e. g. Unified Parkinson's disease rating scale or Beck depression inventory). The analysis is based on parametrization of 5 Czech vowels pronounced by 84 PD patients. Using classification and regression trees we estimated all clinical scores with maximal error lower or equal to 13 %. Best estimation was observed in the case of Mini-mental state examination (MAE = 0.77, estimation error 5.50 %). Finally, we proposed a binary classification based on random forests that is able to identify Parkinson's disease with sensitivity SEN = 92.86% (SPE = 85.71 %). The parametrization process was based on extraction of 107 speech features quantifying different clinical signs of hypokinetic dysarthria present in PD.","PeriodicalId":373170,"journal":{"name":"2015 4th International Work Conference on Bioinspired Intelligence (IWOBI)","volume":"259 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122863730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. G. Vilda, Agustín Álvarez Marquina, M. V. R. Biarge, Victor Nieto Lluis, R. Martínez, M. C. Vicente-Torcal, J. C. Lázaro-Carrascosa
{"title":"Monitoring Parkinson's Disease from phonation improvement by Log Likelihood Ratios","authors":"P. G. Vilda, Agustín Álvarez Marquina, M. V. R. Biarge, Victor Nieto Lluis, R. Martínez, M. C. Vicente-Torcal, J. C. Lázaro-Carrascosa","doi":"10.1109/IWOBI.2015.7160152","DOIUrl":"https://doi.org/10.1109/IWOBI.2015.7160152","url":null,"abstract":"Parkinson's Disease (PD), contrary to other neurodegenerative diseases, supports certain treatments which can improve patients' conditions or at least mitigate disease effects. Treatments, either pharmacological, surgical or rehabilitative need longitudinal monitoring of patients to assess the progression or regression of thier condition, to optimize resources and benefits. As it is well known, PD leaves important marks in phonation, thus correlates obtained from spoken recordings taken at periodic intervals may be used in longitudinal monitoring of PD. The most preferred correlates are mel-cepstral coefficients, distortion features (jitter, shimmer, HNR, PPE, etc.), tremor indicators, or biomechanical coefficients. Feature templates estimated from each periodic evaluation have to be compared to establish potential progression or regression. The present work is devoted to propose a comparison framework based on Log Likelihood Ratios. This methodology shows to be very sensitive and allows a three-band based comparison: pre-treatment status vs post-treatment status in reference to a control subject or to a control population. Results from a database of eight male patients recorded weekly during a month are shown with comments regarding their severity condition. The conclusions derived show that several distortion, biomechanical and tremor features are quite relevant in monitoring PD phonation.","PeriodicalId":373170,"journal":{"name":"2015 4th International Work Conference on Bioinspired Intelligence (IWOBI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125843204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Luis Gómez, Luis Álvarez-León, L. Mazorra, A. Frery
{"title":"Classification of PolSAR imagery by solving a diffusion-reaction system","authors":"Luis Gómez, Luis Álvarez-León, L. Mazorra, A. Frery","doi":"10.1109/IWOBI.2015.7160147","DOIUrl":"https://doi.org/10.1109/IWOBI.2015.7160147","url":null,"abstract":"PolSAR (Polarimetric Synthetic Aperture Radar) imagery classification plays an essential role in monitoring remote sensing data. Such classification is a difficult task due to the speckle noise which appears in these kind of data. Therefore, there is a need to design new efficient methods to classify PolSAR images. In this work, a new approach to classify PolSAR data is proposed. The method relies on simultaneously filtering and classifying pixels within the image through embedding the problem into a diffusion-reaction partial differential equation system. The diffusion term smooths the patches within the image, and the reaction term tends to move the pixel PolSAR values towards the closest (in some sense) representative class. In particular, the method inherits the benefits of speckle filtering reduction by diffusion-like methods. An iterative schema is stated and, by properly selecting the algorithm control parameters, the user may force the classification to evolve according to her/his requirements to account for other image post-processing tasks (i.e. quantitative analysis to monitor deforestation, drought or urban areas growing). Results on real PolSAR data show the performance of the method, which is evaluated both visually and by means of the confusion matrix, showing an average classification rate 87.56%.","PeriodicalId":373170,"journal":{"name":"2015 4th International Work Conference on Bioinspired Intelligence (IWOBI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130569809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multi-parameter health state assessment","authors":"M. Kozlovszky","doi":"10.1109/IWOBI.2015.7160158","DOIUrl":"https://doi.org/10.1109/IWOBI.2015.7160158","url":null,"abstract":"Recent small, ubiquitous and mobile sensor devices are capable to measure a large set of vital parameters. Organism's health status is correlated with the acquired information. We have established a dynamic health status model, which builds from the collected organism's data. The data collection is realized with a multiplatform data acquisition framework (DAQit), which collects multimodal sensor information remotely, provides visualization/alarming services for experts and forwards information towards to the data archive and dispatcher centers for further processing. The dynamic health status model and a mobile DAQ (mDAQ) system enable experts to provide better and more effective remote health status monitoring, large scale population screening, more effective prevention, and support services.","PeriodicalId":373170,"journal":{"name":"2015 4th International Work Conference on Bioinspired Intelligence (IWOBI)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124257359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}