New strategies for finding multiplicative decompositions of probability trees

Probability trees are a powerful data structure for representing probabilistic potentials. However, their complexity can become intractable if they represent a probability distribution over a large set of variables. In this paper, we study the problem of decomposing a probability tree as a product of smaller trees, with the aim of being able to handle bigger probabilistic potentials. We propose exact and approximate approaches and evaluate their behaviour through an extensive set of experiments

4-Dimensional deformation part model for pose estimation using Kalman filter constraints

[EN] The goal of this research work is to improve the accuracy of human pose estimation using the deformation part model without increasing computational complexity. First, the proposed method seeks to improve pose estimation accuracy by adding the depth channel to deformation part model, which was formerly defined based only on RGB channels, to obtain a 4-dimensional deformation part model. In addition, computational complexity can be controlled by reducing the number of joints by taking into account in a reduced 4-dimensional deformation part model. Finally, complete solutions are obtained by solving the omitted joints by using inverse kinematic models. The main goal of this article is to analyze the effect on pose estimation accuracy when using a Kalman filter added to 4-dimensional deformation part model partial solutions. The experiments run with two data sets showing that this method improves pose estimation accuracy compared with state-of-the-art methods and that a Kalman filter helps to increase this accuracy.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was partially financed by Plan Nacional de I + D, Comision Interministerial de Ciencia y Tecnologa (FEDERCICYT) under the project DPI2013-44227-R.Martínez Bertí, E.; Sánchez Salmerón, AJ.; Ricolfe Viala, C. (2017). 4-Dimensional deformation part model for pose estimation using Kalman filter constraints. International Journal of Advanced Robotic Systems. 14(3):1-13. https://doi.org/10.1177/1729881417714230S11314

Bayesian network analysis of software logs for data-driven software maintenance

Software organisations aim to develop and maintain high-quality software systems. Due to large amounts of behaviour data available, software organisations can conduct data-driven software maintenance. Indeed, software quality assurance and improvement programs have attracted many researchers' attention. Bayesian Networks (BNs) are proposed as a log analysis technique to discover poor performance indicators in a system and to explore usage patterns that usually require temporal analysis. For this, an action research study is designed and conducted to improve the software quality and the user experience of a web application using BNs as a technique to analyse software logs. To this aim, three models with BNs are created. As a result, multiple enhancement points have been identified within the application ranging from performance issues and errors to recurring user usage patterns. These enhancement points enable the creation of cards in the Scrum process of the web application, contributing to its data-driven software maintenance. Finally, the authors consider that BNs within quality-aware and data-driven software maintenance have great potential as a software log analysis technique and encourage the community to deepen its possible applications. For this, the applied methodology and a replication package are shared.Junta de Andalucía, Grant/Award Number: P20‐00091; AEI, Grant/Award Number: PID2019‐106758GB‐32/AEI/10.13039/501100011033; Spanish project, Grant/Award Number: PDC2021‐121195‐I00; Spanish Program, Grant/Award Number: BEAGAL18/00064Peer ReviewedPostprint (published version

Influence of operator?s professional experience in the postoperative course after surgical extrac-tion of the impacted lower third molar : a pilot study

Third molars are present in 96.6% of humans, although they do not always erupt completely. Between 9.5% and 73% of them remain impacted. Surgical removal of impacted third molars is the most common practice in oral and maxillofacial surgery. This procedure results in traumatism and, consequently, the postoperative phase will involve symptomatology. It is uncommon to find studies that directly relate postoperative symptomatology and the operator?s experience. The aim of this study was to determine the differences regarding postoperative symp-tomatology in patients undergoing the bilateral extraction of lower impacted third molars and according to the operator?s experience. A prospective cohort double-blind study was conducted in 50 healthy patients (100 molar extractions) to whom both lower third molars were removed by two dentists with different degree of professional experience. The extractions were randomly assigned with a split?mouth design. If an operator extracted the lower third molar on one side, the other operator extracted the contralateral one. The variables studied after four days of postoperative period were Pain (EVA scale), Inflammation and Trismus, in addition to intraoperative time and local anesthesia administered. Statistically significant differences were detected in the time of intervention and in trismus, since the most experienced operator always needed less time and caused higher degree of trismus. However, this does not entail more inflammation or pain in patients, so there are no relevant differences between operators with more or less experience (p>0.05). The postoperative period is more favorable for the most experienced operator, although the results do not vary in a relevant manner between them

Improving lifespan automation for Caenorhabditis elegans by using image processing and a post-processing adaptive data filter

[EN] Automated lifespan determination for C. elegans cultured in standard Petri dishes is challenging. Problems include occlusions of Petri dish edges, aggregation of worms, and accumulation of dirt (dust spots on lids) during assays, etc. This work presents a protocol for a lifespan assay, with two image-processing pipelines applied to different plate zones, and a new data post-processing method to solve the aforementioned problems. Specifically, certain steps in the culture protocol were taken to alleviate aggregation, occlusions, contamination, and condensation problems. This method is based on an active illumination system and facilitates automated image sequence analysis, does not need human threshold adjustments, and simplifies the techniques required to extract lifespan curves. In addition, two image-processing pipelines, applied to different plate zones, were employed for automated lifespan determination. The first image-processing pipeline was applied to a wall zone and used only pixel level information because worm size or shape features were unavailable in this zone. However, the second image-processing pipeline, applied to the plate centre, fused information at worm and pixel levels. Simple death event detection was used to automatically obtain lifespan curves from the image sequences that were captured once daily throughout the assay. Finally, a new post-processing method was applied to the extracted lifespan curves to filter errors. The experimental results showed that the errors in automated counting of live worms followed the Gaussian distribution with a mean of 2.91% and a standard deviation of +/- 12.73% per Petri plate. Post-processing reduced this error to 0.54 +/- 8.18% per plate. The automated survival curve incurred an error of 4.62 +/- 2.01%, while the post-process method reduced the lifespan curve error to approximately 2.24 +/- 0.55%.This study was also supported by the CDTI agency of the Spanish Ministry of Economy and Competitiveness with CIEN project SMARTFOODS, Universitat PolitAcnica de Valencia with Project 20170020-UPV, Plan Nacional de I + D with Project RTI2018-094312-B-I00 and by European FEDER funds. ADM Nutrition, Biopolis SL and Archer Daniels Midland provided support in the form of salaries for authors P. M. Guerola and S. G. Martinez.Puchalt-Rodríguez, JC.; Sánchez Salmerón, AJ.; Ivorra Martínez, E.; Genovés Martínez, S.; Martínez, R.; Martorell Guerola, P. (2020). Improving lifespan automation for Caenorhabditis elegans by using image processing and a post-processing adaptive data filter. Scientific Reports. 10(1):1-14. https://doi.org/10.1038/s41598-020-65619-4114101Brenner, S. The Genetics Of Caenorhabditis Elegans. 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Quantitative Classification and Natural Clustering of Caenorhabditis elegans Behavioral Phenotypes. Genetics 165, 1117 LP–1126 (2003).Geng, W., Cosman, P., Berry, C. C., Feng, Z. & Schafer, W. R. Automatic tracking, feature extraction and classification of C. elegans phenotypes. IEEE Transactions on Biomed. Eng. 51, 1811–1820, https://doi.org/10.1109/TBME.2004.831532 (2004).Jung, S. K., Aleman-Meza, B., Riepe, C. & Zhong,W. QuantWorm: A comprehensive software package for Caenorhabditis elegans phenotypic assays. Plos One 9, https://doi.org/10.1371/journal.pone.0084830 (2014).Kainmueller, D., Jug, F., Rother, C. & Myers, G. Active Graph Matching for Automatic Joint Segmentation and Annotation of C. elegans BT - Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014. 81–88 (Springer International Publishing, Cham, 2014).Mathew, M. D., Mathew, N. D. & Ebert, P. R. WormScan: A Technique for High-Throughput Phenotypic Analysis of Caenorhabditis elegans. 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Factorisation of Probability Trees and its Applications

Bayesian networks can be seen as a factorisation of a joint probability distribution over a set of variables, based on the conditional independence relations amongst the variables. In this paper we show how it is possible to achieve a finer factorisation decomposing the origninal factors in which some conditions hols. The new ideas can be applied to algorithms able to deal wih factorised probabilistic potentials, as Lazy Propagation, Lazy-Penniless and Importance Sampling

Shelf life prediction of expired vacuum-packed chilled smoked salmon based on a KNN tissue segmentation method using hyperspectral images

Ready-to-eat foods that does not receive a heat treatment before being consumed can be at risk of foodborne hazards and spoilage, so it would be of great interest to have a method for monitoring their safety. This work expands on and enhances previous successfully studies with hyperspectral imaging in the SW-NIR range. Specifically, a k-nearest-neighbours model was developed to classify the salmon tissue into white myocommata stripes (fat) and muscle (lean) tissue. Partial Least Squares models developed confirm that a spatial segmentation should be performed before a shelf life model can be calculated. Employing the fat spectra and only the 7 most correlated wavelengths, a support vector machine model was calculated to classify into days 0, 10, 20, 40 and 60 with 87.2% prediction accuracy. These results make the method developed very promising as a non-destructive method to analyse the shelf life of vacuum-packed chilled smoked salmon fillets.This work has been partially funded by the Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria de Espana (INIA - Spanish National Institute for Agriculture and Food Research and Technology) through research project RTA2012-00062-C04-02, support of European FEDER funds and DPI2013-44227-R project.Ivorra Martínez, E.; Sánchez Salmerón, AJ.; Verdú Amat, S.; Barat Baviera, JM.; Grau Meló, R. (2016). Shelf life prediction of expired vacuum-packed chilled smoked salmon based on a KNN tissue segmentation method using hyperspectral images. Journal of Food Engineering. 178:110-116. https://doi.org/10.1016/j.jfoodeng.2016.01.008S11011617

La superación de estereotipos en niños hacia las personas mayores. Análisis de un programa intergeneracional en el contexto socio-educativo

El estudio presentado examina la imagen que poseen los niños de las personas mayores a través de programas intergeneracionales desarrollados entre centros escolares dependientes de la Consejería de Educación de la Región de Murcia (España) y la red de centros sociales del Instituto Murciano de Acción Social (IMAS). En estos dos escenarios, además de detectar la existencia de ciertos estereotipos por parte del alumnado hacia el colectivo mayor, se pretende conocer de que manera inciden y que aspectos pueden cambiar en todo su proceso hasta la finalización del programa. Teniendo en cuenta los aspectos marcados que facilitan la detección de estereotipos, se ha utilizado una metodología de carácter cuantitativo a través de cuestionarios. Entre los resultados más relevantes, se descubre que el desarrollo de estos programas minimiza ciertos prejuicios y estereotipos hacia la vejez, así como un reforzamiento de la imagen positiva hacia las personas mayores por parte de los niños