On potential cognitive abilities in the machine kingdom

The final publication is available at Springer via http://dx.doi.org/10.1007/s11023-012-9299-6Animals, including humans, are usually judged on what they could become, rather than what they are. Many physical and cognitive abilities in the ‘animal kingdom’ are only acquired (to a given degree) when the subject reaches a certain stage of development, which can be accelerated or spoilt depending on how the environment, training or education is. The term ‘potential ability’ usually refers to how quick and likely the process of attaining the ability is. In principle, things should not be different for the ‘machine kingdom’. While machines can be characterised by a set of cognitive abilities, and measuring them is already a big challenge, known as ‘universal psychometrics’, a more informative, and yet more challenging, goal would be to also determine the potential cognitive abilities of a machine. In this paper we investigate the notion of potential cognitive ability for machines, focussing especially on universality and intelligence. We consider several machine characterisations (non-interactive and interactive) and give definitions for each case, considering permanent and temporal potentials. From these definitions, we analyse the relation between some potential abilities, we bring out the dependency on the environment distribution and we suggest some ideas about how potential abilities can be measured. Finally, we also analyse the potential of environments at different levels and briefly discuss whether machines should be designed to be intelligent or potentially intelligent.We thank the anonymous reviewers for their comments, which have helped to significantly improve this paper. This work was supported by the MEC-MINECO projects CONSOLIDER-INGENIO CSD2007-00022 and TIN 2010-21062-C02-02, GVA project PROMETEO/2008/051, the COST - European Cooperation in the field of Scientific and Technical Research IC0801 AT. Finally, we thank three pioneers ahead of their time(s). We thank Ray Solomonoff (1926-2009) and Chris Wallace (1933-2004) for all that they taught us, directly and indirectly. And, in his centenary year, we thank Alan Turing (1912-1954), with whom it perhaps all began.Hernández-Orallo, J.; Dowe, DL. (2013). On potential cognitive abilities in the machine kingdom. Minds and Machines. 23(2):179-210. https://doi.org/10.1007/s11023-012-9299-6S179210232Amari, S., Fujita, N., Shinomoto, S. (1992). Four types of learning curves. Neural Computation 4(4), 605–618.Aristotle (Translation, Introduction, and Commentary by Ross, W.D.) (1924). Aristotle’s Metaphysics. Oxford: Clarendon Press.Barmpalias, G. & Dowe, D. L. (2012). 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Sustainability and Kaizen: Business Model Trends in Healthcare

[EN] Kaizen, or continuous improvement, is a management tool that allows the identification of activities that have no value in the processes examined. This identification leads to the improvement of these processes within any organization and promotes economic and social sustainability, and to a lesser extent environmental sustainability. Kaizen, already widely and successfully employed in the industrial sector, is now being applied in the health sector. However, the health sector tends to publish only the results of how processes have been improved in finely focused areas and the resulting benefits. The majority of the benefits focus on time and cost reduction. In this study, the authors carried out a bibliometric analysis using the Scimat program, which maps the thematic evolution of Kaizen in the health sector and its relationship with sustainability, in order to promote the interest of the health sector for this type of process improvement. The findings confirm that the implementation of Kaizen is recent and constantly evolves and grows, and that it can help economic and social sustainability, and to a lesser extent environmental sustainability.Morell-Santandreu, O.; Santandreu Mascarell, C.; García Sabater, JJ. (2020). Sustainability and Kaizen: Business Model Trends in Healthcare. Sustainability. 12(24):1-28. https://doi.org/10.3390/su122410622S1281224Sepetis, A. (2019). Sustainable Health Care Management in the Greek Health Care Sector. Open Journal of Social Sciences, 07(12), 386-402. doi:10.4236/jss.2019.712030Sustainable Healthcare—Working towards the Paradigm Shift https://www.anhinternational.org/wp-content/uploads/old/files/100617SustainableHealthcare_White-Paper.pdfWeisz, U., Haas, W., Pelikan, J. M., & Schmied, H. (2011). Sustainable Hospitals: A Socio-Ecological Approach. GAIA - Ecological Perspectives for Science and Society, 20(3), 191-198. doi:10.14512/gaia.20.3.10McGain, F., & Naylor, C. (2014). Environmental sustainability in hospitals – a systematic review and research agenda. Journal of Health Services Research & Policy, 19(4), 245-252. doi:10.1177/1355819614534836D’Andreamatteo, A., Ianni, L., Lega, F., & Sargiacomo, M. (2015). Lean in healthcare: A comprehensive review. Health Policy, 119(9), 1197-1209. doi:10.1016/j.healthpol.2015.02.002Norazlan, A. N. I., Habidin, N. F., Roslan, M. H., & Zainudin, M. Z. (2014). Investigation of kaizen blitz and sustainable performance for Malaysian healthcare industry. International Journal of Quality and Innovation, 2(3/4), 272. doi:10.1504/ijqi.2014.066381Patient Safety in Developing and Transitional Countries 2012 www.who.int/patientsafety/research/emro_afro_report.pdfElmontsri, M., Almashrafi, A., Banarsee, R., & Majeed, A. (2017). Status of patient safety culture in Arab countries: a systematic review. BMJ Open, 7(2), e013487. doi:10.1136/bmjopen-2016-013487Paul Brunet, A., & New, S. (2003). Kaizenin Japan: an empirical study. International Journal of Operations & Production Management, 23(12), 1426-1446. doi:10.1108/01443570310506704Ferreira, D. M. C., & Saurin, T. A. (2019). A complexity theory perspective of kaizen: a study in healthcare. Production Planning & Control, 30(16), 1337-1353. doi:10.1080/09537287.2019.1615649Chahal, H., & Fayza, N. A. (2016). An exploratory study on kaizen muda and organisational sustainability: patients’ perspective. International Journal of Lean Enterprise Research, 2(1), 81. doi:10.1504/ijler.2016.078249Ishijima, H., Nishikido, K., Teshima, M., Nishikawa, S., & Gawad, E. A. (2019). Introducing the «5S-KAIZEN-TQM» approach into public hospitals in Egypt. International Journal of Health Care Quality Assurance, 33(1), 89-109. doi:10.1108/ijhcqa-06-2018-0143Mazzocato, P., Stenfors-Hayes, T., von Thiele Schwarz, U., Hasson, H., & Nyström, M. E. (2016). Kaizen practice in healthcare: a qualitative analysis of hospital employees’ suggestions for improvement. BMJ Open, 6(7), e012256. doi:10.1136/bmjopen-2016-012256Gowen, C. R., McFadden, K. L., & Settaluri, S. (2012). Contrasting continuous quality improvement, Six Sigma, and lean management for enhanced outcomes in US hospitals. American Journal of Business, 27(2), 133-153. doi:10.1108/19355181211274442Grove, A. L., Meredith, J. O., MacIntyre, M., Angelis, J., & Neailey, K. (2010). UK health visiting: challenges faced during lean implementation. Leadership in Health Services, 23(3), 204-218. doi:10.1108/17511871011061037Ho, S. K. M. (2010). Integrated lean TQM model for global sustainability and competitiveness. The TQM Journal, 22(2), 143+-158. doi:10.1108/17542731011024264DelliFraine, J. L., Langabeer, J. R., & Nembhard, I. M. (2010). Assessing the Evidence of Six Sigma and Lean in the Health Care Industry. Quality Management in Health Care, 19(3), 211-225. doi:10.1097/qmh.0b013e3181eb140eSouza, J. P. E., & Alves, J. M. (2018). Lean-integrated management system: A model for sustainability improvement. Journal of Cleaner Production, 172, 2667-2682. doi:10.1016/j.jclepro.2017.11.144Costa, L. B. M., & Godinho Filho, M. (2016). Lean healthcare: review, classification and analysis of literature. Production Planning & Control, 27(10), 823-836. doi:10.1080/09537287.2016.1143131Costa, D. G. da, Pasin, S. S., Magalhães, A. M. M. de, Moura, G. M. S. S. de, Rosso, C. B., & Saurin, T. A. (2018). Analysis of the preparation and administration of medications in the hospital context based on Lean thinking. Escola Anna Nery, 22(4). doi:10.1590/2177-9465-ean-2017-0402Van Aken, J., Chandrasekaran, A., & Halman, J. (2016). Conducting and publishing design science research. Journal of Operations Management, 47-48(1), 1-8. doi:10.1016/j.jom.2016.06.004Glover, W. J., Farris, J. A., Van Aken, E. M., & Doolen, T. L. (2011). Critical success factors for the sustainability of Kaizen event human resource outcomes: An empirical study. International Journal of Production Economics, 132(2), 197-213. doi:10.1016/j.ijpe.2011.04.005Glover, W. J., Liu, W., Farris, J. A., & Van Aken, E. M. (2013). Characteristics of established kaizen event programs: an empirical study. International Journal of Operations & Production Management, 33(9), 1166-1201. doi:10.1108/ijopm-03-2011-0119Aij, K. H., & Rapsaniotis, S. (2017). Leadership requirements for Lean versus servant leadership in health care: a systematic review of the literature. Journal of Healthcare Leadership, Volume 9, 1-14. doi:10.2147/jhl.s120166Garcia, S., Cintra, Y., Torres, R. de C. S. R., & Lima, F. G. (2016). Corporate sustainability management: a proposed multi-criteria model to support balanced decision-making. Journal of Cleaner Production, 136, 181-196. doi:10.1016/j.jclepro.2016.01.110The Sustainability Yearbook 2014 https://www.p-plus.nl/resources/articlefiles/SustainabilityYearbook2014.pdfRebelo, M. F., Santos, G., & Silva, R. (2016). 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(2019). El profesional de la información (EPI): Bibliometric and thematic analysis (2006-2017). El Profesional de la Información, 28(4). doi:10.3145/epi.2019.jul.17WOS Database Available from the Spanish Foundation for Science and Technology https://www.recursoscientificos.fecyt.es/Fundación Española para la Ciencia y la Tecnología (FECYT) www.fecyt.esJiménez-García, M., Ruiz-Chico, J., Peña-Sánchez, A. R., & López-Sánchez, J. A. (2020). A Bibliometric Analysis of Sports Tourism and Sustainability (2002–2019). Sustainability, 12(7), 2840. doi:10.3390/su12072840Chiarini, A., Baccarani, C., & Mascherpa, V. (2018). Lean production, Toyota Production System and Kaizen philosophy. The TQM Journal, 30(4), 425-438. doi:10.1108/tqm-12-2017-0178Garcia, J. A. M., Sabater, J. J. G., & Bonavia, T. (2009). The impact of Kaizen Events on improving the performance of automotive components’ first-tier suppliers. 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Toward some operational principles of sustainable development. Ecological Economics, 2(1), 1-6. doi:10.1016/0921-8009(90)90010-

Uncertainty quantification analysis of the biological Gompertz model subject to random fluctuations in all its parameters

[EN] In spite of its simple formulation via a nonlinear differential equation, the Gompertz model has been widely applied to describe the dynamics of biological and biophysical parts of complex systems (growth of living organisms, number of bacteria, volume of infected cells, etc.). Its parameters or coefficients and the initial condition represent biological quantities (usually, rates and number of individual/particles, respectively) whose nature is random rather than deterministic. In this paper, we present a complete uncertainty quantification analysis of the randomized Gomperz model via the computation of an explicit expression to the first probability density function of its solution stochastic process taking advantage of the Liouville-Gibbs theorem for dynamical systems. The stochastic analysis is completed by computing other important probabilistic information of the model like the distribution of the time until the solution reaches an arbitrary value of specific interest and the stationary distribution of the solution. Finally, we apply all our theoretical findings to two examples, the first of numerical nature and the second to model the dynamics of weight of a species using real data.This work has been supported by the Spanish Ministerio de Economia, Industria y Competitividad (MINECO), the Agencia Estatal de Investigacion (AEI) and Fondo Europeo de Desarrollo Regional (FEDER UE) grant MTM2017-89664-P.Bevia, V.; Burgos, C.; Cortés, J.; Navarro-Quiles, A.; Villanueva Micó, RJ. (2020). Uncertainty quantification analysis of the biological Gompertz model subject to random fluctuations in all its parameters. Chaos, Solitons and Fractals. 138:1-12. https://doi.org/10.1016/j.chaos.2020.109908S112138Golec, J., & Sathananthan, S. (2003). Stability analysis of a stochastic logistic model. Mathematical and Computer Modelling, 38(5-6), 585-593. doi:10.1016/s0895-7177(03)90029-xCortés, J. C., Jódar, L., & Villafuerte, L. (2009). Random linear-quadratic mathematical models: Computing explicit solutions and applications. Mathematics and Computers in Simulation, 79(7), 2076-2090. doi:10.1016/j.matcom.2008.11.008Dorini, F. A., Cecconello, M. S., & Dorini, L. B. (2016). On the logistic equation subject to uncertainties in the environmental carrying capacity and initial population density. Communications in Nonlinear Science and Numerical Simulation, 33, 160-173. doi:10.1016/j.cnsns.2015.09.009Dorini, F. A., Bobko, N., & Dorini, L. B. (2016). A note on the logistic equation subject to uncertainties in parameters. Computational and Applied Mathematics, 37(2), 1496-1506. doi:10.1007/s40314-016-0409-6Cortés, J.-C., Navarro-Quiles, A., Romero, J.-V., & Roselló, M.-D. (2019). Analysis of random non-autonomous logistic-type differential equations via the Karhunen–Loève expansion and the Random Variable Transformation technique. Communications in Nonlinear Science and Numerical Simulation, 72, 121-138. doi:10.1016/j.cnsns.2018.12.013Calatayud, J., Cortés, J. C., & Jornet, M. (2019). Improving the approximation of the probability density function of random nonautonomous logistic‐type differential equations. Mathematical Methods in the Applied Sciences, 42(18), 7259-7267. doi:10.1002/mma.5834Casabán, M.-C., Cortés, J.-C., Navarro-Quiles, A., Romero, J.-V., Roselló, M.-D., & Villanueva, R.-J. (2016). Probabilistic solution of the homogeneous Riccati differential equation: A case-study by using linearization and transformation techniques. Journal of Computational and Applied Mathematics, 291, 20-35. doi:10.1016/j.cam.2014.11.028Hesam, S., Nazemi, A. R., & Haghbin, A. (2012). Analytical solution for the Fokker–Planck equation by differential transform method. 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Improving uncertainty in Widmark equation calculations:alcohol volume, strength and density

The Widmark equation is probably the most commonly used calculation for medicolegal purposes. Recently the National Research Council (USA) and the Forensic Science Regulator (UK) have called for the uncertainty of all results to be given with all forensic measurements and calculations. To improve the uncertainty of measurement of results from Widmark calculations we have concentrated on the uncertainties of measurement involved in the calculation of alcohol, that of the volume of alcohol, the concentration of alcohol and the density of alcohol as previous studies have investigated some of the other factors involved . Using experimental studies, the scientific literature and legal statutes, we have determined revised and improved uncertainties of the concentration of ethanol for Widmark calculations for both the USA and UK. Based on the calculations that we have performed we recommend the use of Monte Carlo Simulation for the determination of uncertainty of measurement for Widmark Calculations

Collaboration in sensor network research: an in-depth longitudinal analysis of assortative mixing patterns

Many investigations of scientific collaboration are based on statistical analyses of large networks constructed from bibliographic repositories. These investigations often rely on a wealth of bibliographic data, but very little or no other information about the individuals in the network, and thus, fail to illustrate the broader social and academic landscape in which collaboration takes place. In this article, we perform an in-depth longitudinal analysis of a relatively small network of scientific collaboration (N = 291) constructed from the bibliographic record of a research center involved in the development and application of sensor network and wireless technologies. We perform a preliminary analysis of selected structural properties of the network, computing its range, configuration and topology. We then support our preliminary statistical analysis with an in-depth temporal investigation of the assortative mixing of selected node characteristics, unveiling the researchers' propensity to collaborate preferentially with others with a similar academic profile. Our qualitative analysis of mixing patterns offers clues as to the nature of the scientific community being modeled in relation to its organizational, disciplinary, institutional, and international arrangements of collaboration.Comment: Scientometrics (In press

An Approach for Actions to Prevent Suicides on Commuter and Metro Rail Systems in the United States, MTI Report 12-33

The primary goals of this report are to discuss measures to prevent suicides on commuter and metro rail systems, and to outline an approach for suicide prevention on rail systems. Based on existing literature and analysis of data obtained from the Metrolink system in Southern California, it was found that most suicides occur near station platforms and near access points to the track. Suicides occurred most frequently when relatively more trains were in operation and in areas of high population density. There do not appear to be suicide “hot spots” (e.g., linked to mental hospitals in the proximity, etc.), based on data analyzed for U.S. systems. The suicide prevention measures range from relatively inexpensive signs posting call-for-help suicide hotline information to costly platform barriers that physically prevent people from jumping onto tracks in front of trains. Other prevention measures fall within this range, such as hotlines available at high frequency suicide locations, or surveillance systems that can report possible suicide attempts and provide the opportunity for intervention tactics. Because of the relatively low number of suicides on rail systems, as compared to the overall number of suicides in general, a cost-effective strategy for preventing suicides on rail systems should be approached in a very focused manner. The prevention measures executed by the rail authorities should be focused on the suicides occurring on the rail systems themselves, while the broader problem of suicides should be left to community-based prevention efforts. Moreover, prevention measures, such as surveillance and response, could “piggyback” on surveillance and response systems used for other purposes on the rail systems to make such projects economically feasible