Bayes classifiers for imbalanced traffic accidents datasets

[EN] Traffic accidents data sets are usually imbalanced, where the number of instances classified under the killed or severe injuries class (minority) is much lower than those classified under the slight injuries class (majority). This, however, supposes a challenging problem for classification algorithms and may cause obtaining a model that well cover the slight injuries instances whereas the killed or severe injuries instances are misclassified frequently. Based on traffic accidents data collected on urban and suburban roads in Jordan for three years (2009-2011); three different data balancing techniques were used: under sampling which removes some instances of the majority class, oversampling which creates new instances of the minority class and a mix technique that combines both. In addition, different Bayes classifiers were compared for the different imbalanced and balanced data sets: Averaged One-Dependence Estimators, Weightily Average One-Dependence Estimators, and Bayesian networks in order to identify factors that affect the severity of an accident. The results indicated that using the balanced data sets, especially those created using oversampling techniques, with Bayesian networks improved classifying a traffic accident according to its severity and reduced the misclassification of killed and severe injuries instances. On the other hand, the following variables were found to contribute to the occurrence of a killed causality or a severe injury in a traffic accident: number of vehicles involved, accident pattern, number of directions, accident type, lighting, surface condition, and speed limit. This work, to the knowledge of the authors, is the first that aims at analyzing historical data records for traffic accidents occurring in Jordan and the first to apply balancing techniques to analyze injury severity of traffic accidents. (C) 2015 Elsevier Ltd. All rights reserved.The authors are grateful to the Police Traffic Department in Jordan for providing the data necessary for this research. Griselda Lopez wishes to express her acknowledgement to the regional ministry of Economy, Innovation and Science of the regional government of Andalusia (Spain) for their scholarship to train teachers and researchers in Deficit Areas, which has made this work possible. The authors appreciate the reviewers' comments and effort in order to improve the paper.Mujalli, R.; López-Maldonado, G.; Garach, L. (2016). Bayes classifiers for imbalanced traffic accidents datasets. Accident Analysis & Prevention. 88:37-51. https://doi.org/10.1016/j.aap.2015.12.003S37518

Cheapest-to-Deliver Collateral: A Common Factor Approach

The collateral choice option gives the collateral posting party the opportunity to switch between different collateral currencies which is well-known to impact the asset price. Quantification of the option's value is of practical importance but remains challenging under the assumption of stochastic rates, as it is determined by an intractable distribution which requires involved approximations. Indeed, many practitioners still rely on deterministic spreads between the rates for valuation. We develop a scalable and stable stochastic model of the collateral spreads under the assumption of conditional independence. This allows for a common factor approximation which admits analytical results from which further estimators are obtained. We show that in modelling the spreads between collateral rates, a second order model yields accurate results for the value of the collateral choice option. The model remains precise for a wide range of model parameters and is numerically efficient even for a large number of collateral currencies.Comment: 23 pages, 4 figures, 4 table

Factors Affecting Implementation of the California Childhood Obesity Research Demonstration (CA-CORD) Project, 2013.

IntroductionEcological approaches to health behavior change require effective engagement from and coordination of activities among diverse community stakeholders. We identified facilitators of and barriers to implementation experienced by project leaders and key stakeholders involved in the Imperial County, California, Childhood Obesity Research Demonstration project, a multilevel, multisector intervention to prevent and control childhood obesity.MethodsA total of 74 semistructured interviews were conducted with project leaders (n = 6) and key stakeholders (n = 68) representing multiple levels of influence in the health care, early care and education, and school sectors. Interviews, informed by the Multilevel Implementation Framework, were conducted in 2013, approximately 12 months after year-one project implementation, and were transcribed, coded, and summarized.ResultsRespondents emphasized the importance of engaging parents and of ensuring support from senior leaders of participating organizations. In schools, obtaining teacher buy-in was described as particularly important, given lower perceived compatibility of the intervention with organizational priorities. From a program planning perspective, key facilitators of implementation in all 3 sectors included taking a participatory approach to the development of program materials, gradually introducing intervention activities, and minimizing staff burden. Barriers to implementation were staff turnover, limited local control over food provided by external vendors or school district policies, and limited availability of supportive resources within the broader community.ConclusionProject leaders and stakeholders in all sectors reported similar facilitators of and barriers to implementation, suggesting the possibility for synergy in intervention planning efforts

Extraction of decision rules via imprecise probabilities

"This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of General Systems on 2017, available online: https://www.tandfonline.com/doi/full/10.1080/03081079.2017.1312359"Data analysis techniques can be applied to discover important relations among features. This is the main objective of the Information Root Node Variation (IRNV) technique, a new method to extract knowledge from data via decision trees. The decision trees used by the original method were built using classic split criteria. The performance of new split criteria based on imprecise probabilities and uncertainty measures, called credal split criteria, differs significantly from the performance obtained using the classic criteria. This paper extends the IRNV method using two credal split criteria: one based on a mathematical parametric model, and other one based on a non-parametric model. The performance of the method is analyzed using a case study of traffic accident data to identify patterns related to the severity of an accident. We found that a larger number of rules is generated, significantly supplementing the information obtained using the classic split criteria.This work has been supported by the Spanish "Ministerio de Economia y Competitividad" [Project number TEC2015-69496-R] and FEDER funds.Abellán, J.; López-Maldonado, G.; Garach, L.; Castellano, JG. (2017). Extraction of decision rules via imprecise probabilities. International Journal of General Systems. 46(4):313-331. https://doi.org/10.1080/03081079.2017.1312359S313331464Abellan, J., & Bosse, E. (2018). Drawbacks of Uncertainty Measures Based on the Pignistic Transformation. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 48(3), 382-388. doi:10.1109/tsmc.2016.2597267Abellán, J., & Klir, G. J. (2005). Additivity of uncertainty measures on credal sets. International Journal of General Systems, 34(6), 691-713. doi:10.1080/03081070500396915Abellán, J., & Masegosa, A. R. (2010). An ensemble method using credal decision trees. European Journal of Operational Research, 205(1), 218-226. doi:10.1016/j.ejor.2009.12.003(2003). International Journal of Intelligent Systems, 18(12). doi:10.1002/int.v18:12Abellán, J., Klir, G. J., & Moral, S. (2006). Disaggregated total uncertainty measure for credal sets. International Journal of General Systems, 35(1), 29-44. doi:10.1080/03081070500473490Abellán, J., Baker, R. M., & Coolen, F. P. A. (2011). Maximising entropy on the nonparametric predictive inference model for multinomial data. European Journal of Operational Research, 212(1), 112-122. doi:10.1016/j.ejor.2011.01.020Abellán, J., López, G., & de Oña, J. (2013). Analysis of traffic accident severity using Decision Rules via Decision Trees. Expert Systems with Applications, 40(15), 6047-6054. doi:10.1016/j.eswa.2013.05.027Abellán, J., Baker, R. M., Coolen, F. P. A., Crossman, R. J., & Masegosa, A. R. (2014). Classification with decision trees from a nonparametric predictive inference perspective. Computational Statistics & Data Analysis, 71, 789-802. doi:10.1016/j.csda.2013.02.009Alkhalid, A., Amin, T., Chikalov, I., Hussain, S., Moshkov, M., & Zielosko, B. (2013). Optimization and analysis of decision trees and rules: dynamic programming approach. International Journal of General Systems, 42(6), 614-634. doi:10.1080/03081079.2013.798902Chang, L.-Y., & Chien, J.-T. (2013). Analysis of driver injury severity in truck-involved accidents using a non-parametric classification tree model. Safety Science, 51(1), 17-22. doi:10.1016/j.ssci.2012.06.017Chang, L.-Y., & Wang, H.-W. (2006). Analysis of traffic injury severity: An application of non-parametric classification tree techniques. Accident Analysis & Prevention, 38(5), 1019-1027. doi:10.1016/j.aap.2006.04.009DE CAMPOS, L. M., HUETE, J. F., & MORAL, S. (1994). PROBABILITY INTERVALS: A TOOL FOR UNCERTAIN REASONING. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 02(02), 167-196. doi:10.1142/s0218488594000146DGT. 2011b.Spanish Road Safety Strategy 2011–2020, 222 p. Madrid: Traffic General Directorate.Dolques, X., Le Ber, F., Huchard, M., & Grac, C. (2016). Performance-friendly rule extraction in large water data-sets with AOC posets and relational concept analysis. International Journal of General Systems, 45(2), 187-210. doi:10.1080/03081079.2015.1072927Gray, R. C., Quddus, M. A., & Evans, A. (2008). Injury severity analysis of accidents involving young male drivers in Great Britain. Journal of Safety Research, 39(5), 483-495. doi:10.1016/j.jsr.2008.07.003Guo, J., & Chankong, V. (2002). Rough set-based approach to rule generation and rule induction. International Journal of General Systems, 31(6), 601-617. doi:10.1080/0308107021000034353Huang, H., Chin, H. C., & Haque, M. M. (2008). Severity of driver injury and vehicle damage in traffic crashes at intersections: A Bayesian hierarchical analysis. Accident Analysis & Prevention, 40(1), 45-54. doi:10.1016/j.aap.2007.04.002Kashani, A. T., & Mohaymany, A. S. (2011). Analysis of the traffic injury severity on two-lane, two-way rural roads based on classification tree models. Safety Science, 49(10), 1314-1320. doi:10.1016/j.ssci.2011.04.019Li, X., & Yu, L. (2016). Decision making under various types of uncertainty. International Journal of General Systems, 45(3), 251-252. doi:10.1080/03081079.2015.1086574Mantas, C. J., & Abellán, J. (2014). Analysis and extension of decision trees based on imprecise probabilities: Application on noisy data. Expert Systems with Applications, 41(5), 2514-2525. doi:10.1016/j.eswa.2013.09.050Mayhew, D. R., Simpson, H. M., & Pak, A. (2003). Changes in collision rates among novice drivers during the first months of driving. Accident Analysis & Prevention, 35(5), 683-691. doi:10.1016/s0001-4575(02)00047-7McCartt, A. T., Mayhew, D. R., Braitman, K. A., Ferguson, S. A., & Simpson, H. M. (2009). Effects of Age and Experience on Young Driver Crashes: Review of Recent Literature. Traffic Injury Prevention, 10(3), 209-219. doi:10.1080/15389580802677807Montella, A., Aria, M., D’Ambrosio, A., & Mauriello, F. (2011). Data-Mining Techniques for Exploratory Analysis of Pedestrian Crashes. Transportation Research Record: Journal of the Transportation Research Board, 2237(1), 107-116. doi:10.3141/2237-12Montella, A., Aria, M., D’Ambrosio, A., & Mauriello, F. (2012). Analysis of powered two-wheeler crashes in Italy by classification trees and rules discovery. Accident Analysis & Prevention, 49, 58-72. doi:10.1016/j.aap.2011.04.025De Oña, J., López, G., & Abellán, J. (2013). Extracting decision rules from police accident reports through decision trees. Accident Analysis & Prevention, 50, 1151-1160. doi:10.1016/j.aap.2012.09.006De Oña, J., López, G., Mujalli, R., & Calvo, F. J. (2013). Analysis of traffic accidents on rural highways using Latent Class Clustering and Bayesian Networks. Accident Analysis & Prevention, 51, 1-10. doi:10.1016/j.aap.2012.10.016Pande, A., & Abdel-Aty, M. (2009). Market basket analysis of crash data from large jurisdictions and its potential as a decision support tool. Safety Science, 47(1), 145-154. doi:10.1016/j.ssci.2007.12.001Peek-Asa, C., Britton, C., Young, T., Pawlovich, M., & Falb, S. (2010). Teenage driver crash incidence and factors influencing crash injury by rurality. Journal of Safety Research, 41(6), 487-492. doi:10.1016/j.jsr.2010.10.002Sikora, M., & Wróbel, Ł. (2013). Data-driven adaptive selection of rule quality measures for improving rule induction and filtration algorithms. International Journal of General Systems, 42(6), 594-613. doi:10.1080/03081079.2013.798901Walley, P. (1996). Inferences from Multinomial Data: Learning About a Bag of Marbles. Journal of the Royal Statistical Society: Series B (Methodological), 58(1), 3-34. doi:10.1111/j.2517-6161.1996.tb02065.xWang, Z., & Klir, G. J. (1992). Fuzzy Measure Theory. doi:10.1007/978-1-4757-5303-5Webb, G. I. (2007). Discovering Significant Patterns. Machine Learning, 68(1), 1-33. doi:10.1007/s10994-007-5006-xWitten, I. H., & Frank, E. (2002). Data mining. ACM SIGMOD Record, 31(1), 76-77. doi:10.1145/507338.50735

Evaluation of Injury Severity for Pedestrian VehicleCrashes in Jordan Using Extracted Rules

[EN] Pedestrian safety is a major concern throughout the world because pedestrians are considered to be the most vulnerable roadway users. This paper sought to identify the main factors in pedestrian-vehicle crashes that increase the risk of a fatality or severe injury. Pedestrian-vehicle crashes which occurred in urban and suburban areas in Jordan between 2009 and 2011 were investigated. Extracted rules from Bayesian networks were used to identify factors related to severity of pedestrian-vehicle crashes. To obtain as much information as possible about these factors, three subsets were used. The first and second subsets contain all types of collisions (pedestrian and nonpedestrian), in which the first subset used collision type as a class variable and the second subset used injury severity. The third subset contains pedestrian collisions only and used injury severity as the class variable. The results indicate that when using collision type as the class variable, better performance was obtained and that the following variables increase the risk of fatality or severe injury: roadway type, number of lanes, speed limit, lighting, and adverse weather conditions.Mujalli, R.; Garach, L.; López-Maldonado, G.; Al-Rousan, T. (2019). Evaluation of Injury Severity for Pedestrian VehicleCrashes in Jordan Using Extracted Rules. Journal of Transportation Engineering. 145(7):04019028-1-04019028-13. https://doi.org/10.1061/JTEPBS.0000244S04019028-104019028-13145

Development of safety performance functions for Spanish two-lane rural highways on flat terrain

[EN] Over decades safety performance functions (SPF) have been developed as a tool for traffic safety in order to estimate the number of crashes in a specific road section. Despite the steady progression of methodological innovations in the crash analysis field, many fundamental issues have not been completely addressed. For instance: Is it better to use parsimonious or fully specified models? How should the goodness-of-fit of the models be assessed? Is it better to use a general model for the entire sample or specific models based on sample stratifications? This paper investigates the above issues by means of several SPFs developed using negative binomial regression models for two-lane rural highways in Spain. The models were based on crash data gathered over a 5-year period, using a broad number of explanatory variables related to exposure, geometry, design consistency and roadside features. Results show that the principle of parsimony could be too restrictive and that it provided simplistic models. Most previous studies apply conventional measurements (i.e., R-2, BIC, AIC, etc.) to assess the goodness-of-fit of models. Seldom do studies apply cumulative residual (CURE) analysis as a tool for model evaluation. This paper shows that CURE plots are essential tools for calibrating SPF, while also providing information for possible sample stratification. Previous authors suggest that sample segmentation increases the model accuracy. The results presented here confirm that finding, and show that the number of significant variables in the final models increases with sample stratification. This paper point out that fully models based on sample segmentation and on CURE may provide more useful insights about traffic crashes than general parsimonious models when developing SPF. (C) 2016 Elsevier Ltd. All rights reserved.The authors would like to thank the ERDF of the European Union for financial support via project "Bases para un sistema experto que permita la identificacion probabilistica de Tramos de Concentracion de Crashes (TCA)" under the "Programa Operativo FEDER de Andalucia 2007-2013". We also thank the Public Works Agency and the Regional Ministry of Public Works and Housing of the Regional Government of Andalusia. Griselda Lopez wishes to express her acknowledgement of the regional ministry of Economy, Innovation and Science of the regional government of Andalusia (Spain) for their scholarship to train teachers and researchers in Deficit Areas.Garach, L.; De Oña, J.; López-Maldonado, G.; Baena-Ruiz, L. (2016). Development of safety performance functions for Spanish two-lane rural highways on flat terrain. Accident Analysis & Prevention. 95:250-265. https://doi.org/10.1016/j.aap.2016.07.021S2502659

Host relationships and geographic distribution of species of Blanchard, 1848 (Onchoproteocephalidea, Onchobothriidae) in elasmobranchs: a metadata analysis

Species of Acanthobothrium have been documented as parasites of the spiral intestine of elasmobranchs. Results of a metadata analysis indicate that 114 species of elasmobranchs have been reported as hosts of 200 species of Acanthobothrium. The metadata analysis revealed that 3.7% of species of sharks and 14.9% of species of rays that have been reported as hosts to date; some species are parasitized by more than one species of Acanthobothrium. This work provides a Category designation, as proposed by Ghoshroy and Caira (2001), for each species of Acanthobothrium. These Category designations are a tool to facilitate comparisons among members of Acanthobothrium for descriptions of new species in the future

A proposal for cost-related and market-oriented train running charges

[EN] This paper examines some key aspects of a charging system for promoting railway transport, including charges reflecting a clear relationship with costs (transparency) and charges reflecting the quality of the infrastructure manager¿s service. Train running charges recover track-related costs and can help to develop a charging system that meets these requirements. To orient train running charges to the market, a method for processing track maintenance and renewal costs is proposed whereby the quality of the service provided by an infrastructure is measured according to its utility to the railway undertaking. To achieve transparency, a single indicator is used for cost planning and the subsequent levying of costs on railway undertakings. The paper includes an example of how proposed train running charges would be calculated according to data from 14 European countries. The example shows that short-distance trains generate the lowest maintenance and renewal costs, followed by long-distance trains and freight trains.This work was supported by the Spanish Ministerio de Fomento [grant number PT-2007-056-05CCPP].Calvo, F.; De Oña, J.; De Oña, R.; López-Maldonado, G.; Garach, L. (2014). A proposal for cost-related and market-oriented train running charges. Transportation Planning and Technology. 37(4):354-372. https://doi.org/10.1080/03081060.2014.897127S354372374Baumgartner, J. P. 2001. “Prices and Costs in the Railway Sector.” Laboratoire d'Intermodalité des Transports et de Planification. École Polytechnique Fédérale de Lausanne. Accessed February 4. http://litep.epfl.ch–2014Calvo, F., and J. de Oña. 2012a. “An Approach to Mark-Ups through Capacity Charges.”Proceedings of the ICE – Transport. Accessed February 4. http://www.icevirtuallibrary.com/content/article/10.1680/tran.11.00050.Calvo, F., & De Oña, J. (2012). Are rail charges connected to costs? Journal of Transport Geography, 22, 28-33. doi:10.1016/j.jtrangeo.2011.11.004Calvo, F., de Oña, J., López, G., Garach, L., & de Oña, R. (2013). Rail track costs management for efficient railway charges. Proceedings of the Institution of Civil Engineers - Transport, 166(6), 325-335. doi:10.1680/tran.11.00001Calvo, F., de Oña, J., & Nash, A. (2007). Proposed Infrastructure Pricing Methodology for Mixed-Use Rail Networks. Transportation Research Record: Journal of the Transportation Research Board, 1995(1), 9-16. doi:10.3141/1995-02CENIT, TIS PT, IWW, and HERRY. 2007. “RailCalc. Calculation of Charges for the Use of Rail Infrastructure.” Prepared for the European Commission Directorate General for Energy and Transport. Accessed February 4. http://ec.europa.eu/transport/rail/legislation/doc/railcalc_discussion_paper_final.pdf.ECMT (European Conference of Ministers of Transport). 2005. “Charges for the Use of Infrastructure in ECMT Railways.” Draft final report. ECMT/CS/CF(2005)1/REV1. Accessed February 4. http://lnweb90.worldbank.org/ECA/Transport.nsf/ECADocByUnid/2CF8BE276F63A37D85256FB20043A05D?Opendocument.EPFL (Ecole Polytechnique Féderale de Lausanne). 2003. “IMPROVERAIL: IMPROVEd Tools for RAILway Capacity and Access Management.” Accessed February 4. http://litep.epfl.ch.Network Rail. 2006. “Usage Costs – Assessment Methodology.” Draft for consultation. Accessed February 4. http://www.networkrail.co.uk/browse%20documents/regulatory%20documents/access%20charges%20reviews/consultations%20on%20future%20charging/variable%20track%20access%20charges/g-%20usage%20costs%20methodology%20sept%2006.pdf.Nyström, B., & Söderholm, P. (2010). Selection of maintenance actions using the analytic hierarchy process (AHP): decision-making in railway infrastructure. Structure and Infrastructure Engineering, 6(4), 467-479. doi:10.1080/15732470801990209ORR (Office of Rail Regulation). 2005. “Revision of Variable Usage and Electrification Asset Usage Charges: Final Report.” Accessed February 4. http://www.rail-reg.gov.uk/upload/pdf/bah_variable-usage-initial-report_jan05.pdf.Quinet, E. (2003). Short term adjustments in rail activity: the limited role of infrastructure charges. Transport Policy, 10(1), 73-79. doi:10.1016/s0967-070x(02)00047-1Thomas, J. 2002. “EU Task Force on Rail Infrastructure Charging: Summary Findings on Best Practice in Marginal Cost Pricing.” IMPRINT-EUROPE. Implementing Reform in Transport. Effective Use of Research on Pricing in Europe. A European Commission-funded Thematic Network (2001–2004). Accessed February 4. www.imprint-eu.org/public/Presentations/imprint3_Thomas.ppt.UIC (International Union of Railways). 2008. “Lasting Infrastructure Cost Benchmarking (LICB).” Summary Report. Accessed February 4. http://www.uic.org/spip.php?article582

Aplicación de un software original para el seguimiento de procesos de participación ciudadana

Esta ponencia presenta la utilización de una herramienta tecnológica original para el Seguimiento y Evaluación de Procesos de Interactividad en un Dispositivo Hipermedial Dinámico (SEPI-DHD). Se trabajó sobre un proyecto de integración de diversas Tecnologías de la Información y Comunicación (TIC) para la participación ciudadana implementado en una localidad de la provincia de Santa Fe, Argentina. Dicho proyecto promociona la construcción de la memoria plural de sus habitantes mediante la participación responsable. A tal fin fue necesario profundizar teóricamente en los conceptos de interactividad e interacción en el contexto del siglo XXI como base metodológica para la uso del software. Los diversos resultados obtenidos evidencian de manera cuanticualitativa que los espacios propuestos potenciaron el intercambio y la comunicación de los ciudadanos con fines educativos, comunitarios, políticos y de producción.Presentado en el VI Workshop Arquitectura, Redes y Sistemas Operativos (WARSO)Red de Universidades con Carreras en Informática (RedUNCI

Sensitivities and Hedging of the Collateral Choice Option

The collateral choice option allows a collateral-posting party the opportunity to change the type of security in which the collateral is deposited. Due to non-zero collateral basis spreads, this optionality significantly impacts asset valuation. Because of the complexity of valuing the option, many practitioners resort to deterministic assumptions on the collateral rates. In this article, we focus on a valuation model of the collateral choice option based on stochastic dynamics. Intrinsic differences in the resulting collateral choice option valuation and its implications for collateral management are presented. We obtain sensitivities of the collateral choice option price under both the deterministic and the stochastic model, and we show that the stochastic model attributes risks to all involved collateral currencies. Besides an inability to capture volatility effects, the deterministic model exhibits a digital structure in which only the cheapest-to-deliver currency influences the valuation at a given time. We further consider hedging an asset with the collateral choice option by a portfolio of domestic and foreign zero-coupon bonds that do not carry the collateral choice option. We propose static hedging strategies based on the crossing times of the deterministic model and based on variance-minimization under the stochastic model. We show how the weights of this model can be explicitly determined with the semi-analytical common factor approach and we show in numerical experiments that this strategy offers good hedging performance under minimized variance