Theorical aspects in measurement of impacts on social environment of special wastes

La gestión de los residuos tóxicos y\ud peligrosos es uno de los objetivos prioritarios en los países desarrollados. Los planes elaborados para ello deben considerar tanto el posible impacto\ud ambiental que provocan las instalaciones de tratamiento como el posible efecto sobre el medio social. El objetivo de este trabajo es la discusión conceptual de los efectos de los centros de gestión de residuos en el medio social y la selección de los\ud indicadores apropiados a partir de la encuesta directa a expenos y AdministraciónThe management of toxic an dangerous waste is one of the main goal of the development countries. The plans elaborated by those countries must consider, the posible environmental impact\ud that produce the treatment facilities and the effect\ud upon the social environment. The objetive of this work is the discussion of the effects of the management waste centers upon the social environment\ud and the selection of the appropiate variables based\ud on direct questionaries to experts and administrations

Agronomic iron-biofortification by activated hydrochars of spent coffee grounds

This work was supported by projects PY20_00585 and RDPTC-2018 (AT17_6096_OTRI UGR) from Andalusian Ministry of Economic Transformation, Knowledge, Industry and Universities and FEDER.Iron biofortification has been of main interest for tackling iron deficiency anemia, one of the highest prevalence among micronutrient deficiencies (hidden hunger) in developing countries. This study investigated the effect of activated spent coffee grounds (SCG) and its hydrochars at three temperatures (160 degrees C, 180 degrees C, 200 degrees C) as bio-chelates to level up the iron content of lettuce. Four bio-chelates (ASCG-Fe, AH160-Fe, AH180-Fe and AH200-Fe) were obtained by activation and Fe-functionalization. A pot trial was conducted at doses of 0.2% of the bio-chelates on lettuce with two controls: soil without biofortifying agents (control) and a commercial chelate (control-Fe). Outcomes showed no significant differences (p < 0.05) in soil properties nor in plant growth and morphology, indicating absence of phytotoxicity. All bio-chelates enhanced iron content of plants between 41% (AH200-Fe) and 150% (AH160-Fe) compared to control. The best biofortification effect performed by AH160-Fe was similar to control-Fe (169%), also in terms of soil-plant efficiency both products showed the same transfer factor of 0.07. A proportional impact (up to 150%) was seen on the contribution to the recommended daily intake (RDI). Moreover, higher contents of Mn (29%) and Cu (133%) was evidenced in lettuce with the application of ASCG-Fe and AH180-Fe. These findings suggest activated SCG hydrochars, better than SCG, at small (sub-toxic) doses can successfully achieve agronomic iron biofortification.Andalusian Ministry of Economic Transformation, Knowledge, Industry and Universities PY20_00585, RDPTC-2018 (AT17_6096_OTRI UGR)FEDE

Relación entre recién nacidos de alto riesgo y sus padres, algunas reflexiones psicodinámicas.

Se analizan las interrelaciones entre recién nacidos de alto riesgo y sus padres, así como las repercusiones que el ingreso temprano condiciona en la asunción de los papeles de los padres. Se destaca la labor del profesional en la doble vertiente de la actuación sobre el niño y sobre la pareja. Se constata la importancia de una actuación a este nivel del profesional en salud mental como transmisor de información y estimulador de las figuras paternas en la asunción de sus roles y preventivamente sobre el futuro psicológico del niño

Analyzing of Gender Behaviors from Paths Using Process Mining: A Shopping Mall Application

[EN] The study presents some results of customer paths¿ analysis in a shopping mall. Bluetooth-based technology is used to collect data. The event log containing spatiotemporal information is analyzed with process mining. Process mining is a technique that enables one to see the whole process contrary to data-centric methods. The use of process mining can provide a readily-understandable view of the customer paths. We installed iBeacon devices, a Bluetooth-based positioning system, in the shopping mall. During December 2017 and January and February 2018, close to 8000 customer data were captured. We aim to investigate customer behaviors regarding gender by using their paths. We can determine the gender of customers if they go to the men¿s bathroom or women¿s bathroom. Since the study has a comprehensive scope, we focused on male and female customers¿ behaviors. This study shows that male and female customers have different behaviors. Their duration and paths, in general, are not similar. In addition, the study shows that the process mining technique is a viable way to analyze customer behavior using Bluetooth-based technology.Dogan, O.; Bayo-Monton, JL.; Fernández Llatas, C.; Oztaysi, B. (2019). Analyzing of Gender Behaviors from Paths Using Process Mining: A Shopping Mall Application. Sensors. 19(3):1-20. https://doi.org/10.3390/s19030557S120193Oosterlinck, D., Benoit, D. F., Baecke, P., & Van de Weghe, N. (2017). Bluetooth tracking of humans in an indoor environment: An application to shopping mall visits. Applied Geography, 78, 55-65. doi:10.1016/j.apgeog.2016.11.005Merad, D., Aziz, K.-E., Iguernaissi, R., Fertil, B., & Drap, P. (2016). Tracking multiple persons under partial and global occlusions: Application to customers’ behavior analysis. Pattern Recognition Letters, 81, 11-20. doi:10.1016/j.patrec.2016.04.011Wu, Y., Wang, H.-C., Chang, L.-C., & Chou, S.-C. (2015). Customer’s Flow Analysis in Physical Retail Store. Procedia Manufacturing, 3, 3506-3513. doi:10.1016/j.promfg.2015.07.672Dogan, O., & Öztaysi, B. (2018). In-store behavioral analytics technology selection using fuzzy decision making. Journal of Enterprise Information Management, 31(4), 612-630. doi:10.1108/jeim-02-2018-0035Hwang, I., & Jang, Y. J. (2017). Process Mining to Discover Shoppers’ Pathways at a Fashion Retail Store Using a WiFi-Base Indoor Positioning System. IEEE Transactions on Automation Science and Engineering, 14(4), 1786-1792. doi:10.1109/tase.2017.2692961Abedi, N., Bhaskar, A., Chung, E., & Miska, M. (2015). Assessment of antenna characteristic effects on pedestrian and cyclists travel-time estimation based on Bluetooth and WiFi MAC addresses. Transportation Research Part C: Emerging Technologies, 60, 124-141. doi:10.1016/j.trc.2015.08.010Mou, S., Robb, D. J., & DeHoratius, N. (2018). Retail store operations: Literature review and research directions. European Journal of Operational Research, 265(2), 399-422. doi:10.1016/j.ejor.2017.07.003Fernandez-Llatas, C., Lizondo, A., Monton, E., Benedi, J.-M., & Traver, V. (2015). Process Mining Methodology for Health Process Tracking Using Real-Time Indoor Location Systems. Sensors, 15(12), 29821-29840. doi:10.3390/s151229769Van der Aalst, W. M. P., van Dongen, B. F., Herbst, J., Maruster, L., Schimm, G., & Weijters, A. J. M. M. (2003). Workflow mining: A survey of issues and approaches. Data & Knowledge Engineering, 47(2), 237-267. doi:10.1016/s0169-023x(03)00066-1Ou-Yang, C., & Winarjo, H. (2011). Petri-net integration – An approach to support multi-agent process mining. Expert Systems with Applications, 38(4), 4039-4051. doi:10.1016/j.eswa.2010.09.066Partington, A., Wynn, M., Suriadi, S., Ouyang, C., & Karnon, J. (2015). Process Mining for Clinical Processes. ACM Transactions on Management Information Systems, 5(4), 1-18. doi:10.1145/2629446Yoo, S., Cho, M., Kim, E., Kim, S., Sim, Y., Yoo, D., … Song, M. (2016). Assessment of hospital processes using a process mining technique: Outpatient process analysis at a tertiary hospital. International Journal of Medical Informatics, 88, 34-43. doi:10.1016/j.ijmedinf.2015.12.018Funkner, A. A., Yakovlev, A. N., & Kovalchuk, S. V. (2017). Towards evolutionary discovery of typical clinical pathways in electronic health records. Procedia Computer Science, 119, 234-244. doi:10.1016/j.procs.2017.11.181Jans, M., Alles, M., & Vasarhelyi, M. (2013). The case for process mining in auditing: Sources of value added and areas of application. International Journal of Accounting Information Systems, 14(1), 1-20. doi:10.1016/j.accinf.2012.06.015Yoshimura, Y., Sobolevsky, S., Ratti, C., Girardin, F., Carrascal, J. P., Blat, J., & Sinatra, R. (2014). An Analysis of Visitors’ Behavior in the Louvre Museum: A Study Using Bluetooth Data. Environment and Planning B: Planning and Design, 41(6), 1113-1131. doi:10.1068/b130047pDe Leoni, M., van der Aalst, W. M. P., & Dees, M. (2016). A general process mining framework for correlating, predicting and clustering dynamic behavior based on event logs. Information Systems, 56, 235-257. doi:10.1016/j.is.2015.07.003Rebuge, Á., & Ferreira, D. R. (2012). Business process analysis in healthcare environments: A methodology based on process mining. Information Systems, 37(2), 99-116. doi:10.1016/j.is.2011.01.003Arroyo, R., Yebes, J. J., Bergasa, L. M., Daza, I. G., & Almazán, J. (2015). Expert video-surveillance system for real-time detection of suspicious behaviors in shopping malls. Expert Systems with Applications, 42(21), 7991-8005. doi:10.1016/j.eswa.2015.06.016Popa, M. C., Rothkrantz, L. J. M., Shan, C., Gritti, T., & Wiggers, P. (2013). Semantic assessment of shopping behavior using trajectories, shopping related actions, and context information. Pattern Recognition Letters, 34(7), 809-819. doi:10.1016/j.patrec.2012.04.015Kang, L., & Hansen, M. (2017). Behavioral analysis of airline scheduled block time adjustment. Transportation Research Part E: Logistics and Transportation Review, 103, 56-68. doi:10.1016/j.tre.2017.04.004Rovani, M., Maggi, F. M., de Leoni, M., & van der Aalst, W. M. P. (2015). Declarative process mining in healthcare. Expert Systems with Applications, 42(23), 9236-9251. doi:10.1016/j.eswa.2015.07.040Fernández-Llatas, C., Benedi, J.-M., García-Gómez, J., & Traver, V. (2013). Process Mining for Individualized Behavior Modeling Using Wireless Tracking in Nursing Homes. Sensors, 13(11), 15434-15451. doi:10.3390/s131115434Van der Aalst, W. M. P., Reijers, H. A., Weijters, A. J. M. M., van Dongen, B. F., Alves de Medeiros, A. K., Song, M., & Verbeek, H. M. W. (2007). Business process mining: An industrial application. Information Systems, 32(5), 713-732. doi:10.1016/j.is.2006.05.003M. Valle, A., A.P. Santos, E., & R. Loures, E. (2017). Applying process mining techniques in software process appraisals. Information and Software Technology, 87, 19-31. doi:10.1016/j.infsof.2017.01.004Juhaňák, L., Zounek, J., & Rohlíková, L. (2019). Using process mining to analyze students’ quiz-taking behavior patterns in a learning management system. Computers in Human Behavior, 92, 496-506. doi:10.1016/j.chb.2017.12.015Sedrakyan, G., De Weerdt, J., & Snoeck, M. (2016). Process-mining enabled feedback: «Tell me what I did wrong» vs. «tell me how to do it right». Computers in Human Behavior, 57, 352-376. doi:10.1016/j.chb.2015.12.040Schoor, C., & Bannert, M. (2012). Exploring regulatory processes during a computer-supported collaborative learning task using process mining. Computers in Human Behavior, 28(4), 1321-1331. doi:10.1016/j.chb.2012.02.016Werner, M., & Gehrke, N. (2015). Multilevel Process Mining for Financial Audits. IEEE Transactions on Services Computing, 8(6), 820-832. doi:10.1109/tsc.2015.2457907De Weerdt, J., Schupp, A., Vanderloock, A., & Baesens, B. (2013). Process Mining for the multi-faceted analysis of business processes—A case study in a financial services organization. Computers in Industry, 64(1), 57-67. doi:10.1016/j.compind.2012.09.010Herbert, L., Hansen, Z. N. L., Jacobsen, P., & Cunha, P. (2014). Evolutionary Optimization of Production Materials Workflow Processes. Procedia CIRP, 25, 53-60. doi:10.1016/j.procir.2014.10.010Yim, J., Jeong, S., Gwon, K., & Joo, J. (2010). Improvement of Kalman filters for WLAN based indoor tracking. Expert Systems with Applications, 37(1), 426-433. doi:10.1016/j.eswa.2009.05.047Delafontaine, M., Versichele, M., Neutens, T., & Van de Weghe, N. (2012). Analysing spatiotemporal sequences in Bluetooth tracking data. Applied Geography, 34, 659-668. doi:10.1016/j.apgeog.2012.04.003Frisby, J., Smith, V., Traub, S., & Patel, V. L. (2017). Contextual Computing : A Bluetooth based approach for tracking healthcare providers in the emergency room. Journal of Biomedical Informatics, 65, 97-104. doi:10.1016/j.jbi.2016.11.008Yoshimura, Y., Krebs, A., & Ratti, C. (2017). Noninvasive Bluetooth Monitoring of Visitors’ Length of Stay at the Louvre. IEEE Pervasive Computing, 16(2), 26-34. doi:10.1109/mprv.2017.33Cao, Q., Jones, D. R., & Sheng, H. (2014). Contained nomadic information environments: Technology, organization, and environment influences on adoption of hospital RFID patient tracking. Information & Management, 51(2), 225-239. doi:10.1016/j.im.2013.11.007Larson, J. S., Bradlow, E. T., & Fader, P. S. (2005). An exploratory look at supermarket shopping paths. 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Relación entre recién nacidos de alto riesgo y sus padres, algunas reflexiones psicodinámicas.

Se analizan las interrelaciones entre recién nacidos de alto riesgo y sus padres, así como las repercusiones que el ingreso temprano condiciona en la asunción de los papeles de los padres. Se destaca la labor del profesional en la doble vertiente de la actuación sobre el niño y sobre la pareja. Se constata la importancia de una actuación a este nivel del profesional en salud mental como transmisor de información y estimulador de las figuras paternas en la asunción de sus roles y preventivamente sobre el futuro psicológico del niño

Development and implantation of two teleradiology and teleconsulting applications in Catalunya: RAIM and CARE

Two teleradiology applications with the added-value of teleconsulting are described: CARE, a high level diagnostic oriented application with videoconference and image and cursor synchronization based on SUN stations, and RAIM, a lower level PC-based application oriented to the transmission of patients' results, reports and associated images. Their technical characteristics and solutions adopted are presented together with the context in which they have been developed and thought to fit in.Peer ReviewedPostprint (published version

Subinspectores de Empleo y Seguridad Social (Caso práctico): [Orden TIN/2216/2010, de 2 de agosto, por la que se convocan pruebas selectivas para ingreso en el Cuerpo de Subinspectores de Empleo y Seguridad Social]

This case study reproduces the formulation of the case study related to the activity of the Subinspection of Employment and Social Security set out as third exercise in de official announcement of the competitive examination for the entrance to the Body of Subinspectors of Employment and Social Security of the year 2010 (Order TIN/2216/2010). Here it is carried out an analysis of the questions derived from the exposition, incorporating the legal reasoning of the answer.El presente caso práctico reproduce el enunciado del supuesto referido a la actividad de la Subinspección de Empleo y Seguridad Social planteado como tercer ejercicio en la convocatoria de la oposición para el ingreso en el Cuerpo de Subinspectores de Empleo y Seguridad Social correspondiente a 2010 (Orden TIN/2216/2010). En él se efectúa un análisis de las cuestiones derivadas del planteamiento, incorporando la fundamentación jurídica de la respuesta

SVD Applied to Voltage Sag State Estimation

The method presented in this paper addresses the problem of voltage sag state estimation (VSSE). The problem consists in estimating the voltage sags frequency at non-monitored buses from the number of sags measured at monitored sites. Usually, due to limitations on the number of available voltage sag monitors, this is an underdetermined problem. In this approach, the mathematical formulation presented is based on the fault positions concept and is solved by means of the Singular Value Decomposition (SVD) technique. The proposed estimation method has been validated by using the IEEE 118 test system and the results obtained have been very satisfactory