Reverse engineering applied to biomodelling and pathological bone manufacturing using FDM technology

[EN] Reverse engineering and medical image-based modeling technologies allow manufacturing of 3D biomodels of anatomical structures of human body. These techniques are based on anatomical information from scanning data such as CT and MRI, whose scanners are used for scanning data acquisition of the external and internal geometry of anatomical structures. These 3D biomodels have many medical applications such surgical training, preoperative planning, surgical simulation, diagnosis and treatments. 3D virtual models of human body structures based on CT are increasingly being used in clinical practice. A data processing methodology is required to obtain an accurate 3D model suitable for manufacturing using AM, and specially the FDM technologies. This study shows a step-by-step methodology to process the CT information in bounded uncertainty conditions in order to obtain the STL models of the degenerated bone components, and to manufacture the 3D biomodels for surgery analysis with optimal design and details, and with an adequate accuracy to ensure proper results by surgeons analysis.The authors wish to acknowledge the support of Ms. Jerica Risent and Mr. Joan Ortiz of Ford Motor Company for his assistance in the scanning of printed models. This work was supported by the Polisabio Funding (UPV-Fisabio 2017)Laura Piles; Miguel J. Reig; Vte. Jesús Seguí; Rafael Pla; Fernando Martínez; José Miguel Seguí (2019). Reverse engineering applied to biomodelling and pathological bone manufacturing using FDM technology. Procedia Manufacturing. 41:739-746. https://doi.org/10.1016/j.promfg.2019.09.065S73974641Van Eijnatten, M., Berger, F. H., de Graaf, P., Koivisto, J., Forouzanfar, T., & Wolff, J. (2017). Influence of CT parameters on STL model accuracy. Rapid Prototyping Journal, 23(4), 678-685. doi:10.1108/rpj-07-2015-0092Lalone, E. A., Willing, R. T., Shannon, H. L., King, G. J. W., & Johnson, J. A. (2015). Accuracy assessment of 3D bone reconstructions using CT: an intro comparison. Medical Engineering & Physics, 37(8), 729-738. doi:10.1016/j.medengphy.2015.04.010Stull, K. E., Tise, M. L., Ali, Z., & Fowler, D. R. (2014). Accuracy and reliability of measurements obtained from computed tomography 3D volume rendered images. Forensic Science International, 238, 133-140. doi:10.1016/j.forsciint.2014.03.005Van Eijnatten, M., van Dijk, R., Dobbe, J., Streekstra, G., Koivisto, J., & Wolff, J. (2018). CT image segmentation methods for bone used in medical additive manufacturing. Medical Engineering & Physics, 51, 6-16. doi:10.1016/j.medengphy.2017.10.008Javaid, M., & Haleem, A. (2018). Additive manufacturing applications in medical cases: A literature based review. Alexandria Journal of Medicine, 54(4), 411-422. doi:10.1016/j.ajme.2017.09.003D.V.C. Stoffelen, K. Eraly, P. Debeer, The use of 3D printing technology in reconstruction of a severe glenoid defect: a case report with 2.5 years of follow-up, Journal of Shoulder Elbow Surgery, 24 (2015) e218-e22

Considerations about quality in model-driven engineering

The final publication is available at Springer via http://dx.doi.org/10.1007/s11219-016-9350-6The virtue of quality is not itself a subject; it depends on a subject. In the software engineering field, quality means good software products that meet customer expectations, constraints, and requirements. Despite the numerous approaches, methods, descriptive models, and tools, that have been developed, a level of consensus has been reached by software practitioners. However, in the model-driven engineering (MDE) field, which has emerged from software engineering paradigms, quality continues to be a great challenge since the subject is not fully defined. The use of models alone is not enough to manage all of the quality issues at the modeling language level. In this work, we present the current state and some relevant considerations regarding quality in MDE, by identifying current categories in quality conception and by highlighting quality issues in real applications of the model-driven initiatives. We identified 16 categories in the definition of quality in MDE. From this identification, by applying an adaptive sampling approach, we discovered the five most influential authors for the works that propose definitions of quality. These include (in order): the OMG standards (e.g., MDA, UML, MOF, OCL, SysML), the ISO standards for software quality models (e.g., 9126 and 25,000), Krogstie, Lindland, and Moody. We also discovered families of works about quality, i.e., works that belong to the same author or topic. Seventy-three works were found with evidence of the mismatch between the academic/research field of quality evaluation of modeling languages and actual MDE practice in industry. We demonstrate that this field does not currently solve quality issues reported in industrial scenarios. The evidence of the mismatch was grouped in eight categories, four for academic/research evidence and four for industrial reports. These categories were detected based on the scope proposed in each one of the academic/research works and from the questions and issues raised by real practitioners. We then proposed a scenario to illustrate quality issues in a real information system project in which multiple modeling languages were used. For the evaluation of the quality of this MDE scenario, we chose one of the most cited and influential quality frameworks; it was detected from the information obtained in the identification of the categories about quality definition for MDE. We demonstrated that the selected framework falls short in addressing the quality issues. Finally, based on the findings, we derive eight challenges for quality evaluation in MDE projects that current quality initiatives do not address sufficiently.F.G, would like to thank COLCIENCIAS (Colombia) for funding this work through the Colciencias Grant call 512-2010. This work has been supported by the Gene-ralitat Valenciana Project IDEO (PROMETEOII/2014/039), the European Commission FP7 Project CaaS (611351), and ERDF structural funds.Giraldo-Velásquez, FD.; España Cubillo, S.; Pastor López, O.; Giraldo, WJ. (2016). Considerations about quality in model-driven engineering. Software Quality Journal. 1-66. https://doi.org/10.1007/s11219-016-9350-6S166(1985). Iso information processing—documentation symbols and conventions for data, program and system flowcharts, program network charts and system resources charts. ISO 5807:1985(E) (pp. 1–25).(2011). Iso/iec/ieee systems and software engineering – architecture description. 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The Development of Teaching Material of Physics Introductory for Biology with Science, Technology, Engineering, and Mathematics (STEM) Approach

Journal of Physics: Conference Series PAPER • THE FOLLOWING ARTICLE ISOPEN ACCESS The Development of Teaching Material of Physics Introductory for Biology with Science, Technology, Engineering, and Mathematics (STEM) Approach Muhammad Aswin Rangkuti1, Winsyahputra Ritonga1 and Wasis Wuyung Wisnu Brata2 Published under licence by IOP Publishing Ltd Journal of Physics: Conference Series, Volume 1462, The 6th Annual International Seminar on Trends in Science and Science Education 16–17 October 2019, North Sumatera Province, Indonesia Citation Muhammad Aswin Rangkuti et al 2020 J. Phys.: Conf. Ser. 1462 012038 DownloadArticle PDF References 90 Total downloads Turn on MathJax Share this article Share this content via email Share on Facebook Share on Twitter Share on Google+ Share on Mendeley Article information Abstract In higher education, many concepts in physics are applied in various disciplines that explain the development of the theory they learn; one of them is Physics Introductory. Natural Science Students, such as Biology and Chemistry, unwittingly use many essential concepts of Physics. However, the learning process in this course generally only explains concepts in Physics without relating them to the needs of interdisciplinary knowledge. As a result, interdisciplinary students feel that Physics is meaningless and not applicable. This raises the perception that causes them not interested to learn Physics. In fact, the concepts contained in this course are very important for the development of their knowledge. This research will try to rearrange the materials in the Physics introductory course linked to the Biology concepts. The development of teaching materials uses the Research and Development (R & D) method. This paper will discuss theories and publications that support the importance of interdisciplinary integrated learning. Furthermore, the development of teaching material and its effectiveness will be discussed in our future publication

A Practical Procedure to Integrate the First 1:500 Urban Map of Valencia into a Tile-Based Geospatial Information System

[EN] The use of geographic data from early maps is a common approach to understanding urban geography as well as to study the evolution of cities over time. The specific goal of this paper is to provide a means for the integration of the first 1:500 urban map of the city of Valencia (Spain) on a tile-based geospatial system. We developed a workflow consisting of three stages: the digitization of the original 421 map sheets, the transformation to the European Terrestrial Reference System of 1989 (ETRS89), and the conversion to a tile-based file format, where the second stage is clearly the most mathematically involved. The second stage actually consists of two steps, one transformation from the pixel reference system to the 1929 local reference system followed by a second transformation from the 1929 local to the ETRS89 system. The last stage comprises a map reprojection to adapt to tile-based geospatial standards. The paper describes a pilot study of one map sheet and results showed that the affine and bilinear transformations performed well in both transformations with average residuals under 6 and 3 cm respectively. The online viewer developed in this study shows that the derived tile-based map conforms to common standards and lines up well with other raster and vector datasets.Villar-Cano, M.; Jiménez-Martínez, MJ.; Marqués-Mateu, Á. (2019). A Practical Procedure to Integrate the First 1:500 Urban Map of Valencia into a Tile-Based Geospatial Information System. ISPRS International Journal of Geo-Information. 8(9). https://doi.org/10.3390/ijgi809037837889Bitelli, G., & Gatta, G. (2011). Digital Processing and 3D Modelling of an 18th Century Scenographic Map of Bologna. Advances in Cartography and GIScience. Volume 2, 129-146. doi:10.1007/978-3-642-19214-2_9Brovelli, M. A., Minghini, M., Giori, G., & Beretta, M. (2012). Web Geoservices and Ancient Cadastral Maps: The Web C.A.R.T.E. Project. Transactions in GIS, 16(2), 125-142. doi:10.1111/j.1467-9671.2012.01311.xBitelli, G., Cremonini, S., & Gatta, G. (2014). Cartographic heritage: Toward unconventional methods for quantitative analysis of pre-geodetic maps. Journal of Cultural Heritage, 15(2), 183-195. doi:10.1016/j.culher.2013.04.003Cardesín Díaz, J. M., & Araujo, J. M. (2016). Historic Urbanization Process in Spain (1746–2013). Journal of Urban History, 43(1), 33-52. doi:10.1177/0096144215583481Villar-Cano, M., Marqués-Mateu, Á., & Jiménez-Martínez, M. J. (2019). Triangulation network of 1929–1944 of the first 1:500 urban map of València. Survey Review, 52(373), 317-329. doi:10.1080/00396265.2018.1564599Chen, W., & Hill, C. (2005). Evaluation Procedure for Coordinate Transformation. Journal of Surveying Engineering, 131(2), 43-49. doi:10.1061/(asce)0733-9453(2005)131:2(43)ISO 19157:2013: Geographic Information—Data Qualityhttps://www.iso.org/standard/32575.htmlASPRS Positional Accuracy Standards for Digital Geospatial Datahttps://www.asprs.org/news-resources/asprs-positional-accuracy-standards-for-digital-geospatial-dataEven-Tzur, G. (2018). Coordinate transformation with variable number of parameters. Survey Review, 52(370), 62-68. doi:10.1080/00396265.2018.1517477Yuanxi, Y., & Tianhe, X. (2002). Combined method of datum transformation between different coordinate systems. Geo-spatial Information Science, 5(4), 5-9. doi:10.1007/bf02826467Lehmann, R. (2014). Transformation model selection by multiple hypotheses testing. Journal of Geodesy, 88(12), 1117-1130. doi:10.1007/s00190-014-0747-

Development of Pisa 2015 Based Chemical Literacy Assessment Instrument For High School Students

This study aims to develop valid and reliable chemical literacy assessment instruments based on PISA 2015. The development procedures carried out were 1) research and information collecting, 2) planning, 3) development preliminary form of product, 4) preliminary field testing, and 5) main product revision. Instrument of development result was validated(content validity and empirical validity). Content validity assessment data was obtained from the validity test results from two chemistry lecturers. Empirical validity test data were acquired from68 grade XI students as test subjects who came from five high schools in Malang. An empirical validity test was used to obtain the level of validity, reliability, discrimination index, difficulty level, and effectiveness of distractors of the items developed in the instrument. The instrument of development results consisted of 20 multiple choice items and 4 attitude questionnaires. The results of the content validity test indicated a valid instrument (the average score for the aspects of substance, construction, and language was 83.9). The results of the empirical validity test showed that multiple-choice items had a correlation value of 0.37-0.77, categorized as valid, and the reliability value was 0.86, classified as highly reliable. The discrimination index obtained was five items ranked as sufficiently good and 15 items categorized as good, while five items classified as easy item, 14 moderate items, and one difficult item, all distractors were functioning. The empirical validity test results in the form of an attitude questionnaire showed a correlation value of 0.65-0.69, so they were valid, and the reliability value was 0.59, classified as quite high criteria. Instrument development results proved to be valid and reliable, so it is feasible to be used to measure students' chemical literacy skills.ReferencesAmerican Association for the Advancement of Science (AAAS). (1993). Benchmarks for science literacy: a project 2061 report. New York: Oxford University Press.Arikunto, S. (1993). Dasar-Dasar Evaluasi Pendidikan. Jakarta: Bumi Aksara.Bond, D. (1989). In Pursuit of Chemical Literacy: A Place for Chemical Reactions. Journal of Chemical Education, 66(2), 157.Celik, S. (2014).Chemical Literacy Levels of Science And Mathematics Teacher Candidates. Australian Journal of Teacher Education, 39(1), 1 – 15Cigdemoglu, C., & Geban, O. (2015). Improving Students' Chemical Literacy Level on Thermochemical And Thermodynamics Concepts through Context-Based Approach. Chemistry Education Research And Practice, 16, 302 – 317.Cigdemoglu, C., Arslan, H. O., & Cam, A. (2017).Argumentation to Foster Pre-Service Science Teachers' Knowledge, Competency, And Attitude on The Domains of Chemical Literacy of Acids And Bases. Chemistry Education Research And Practice, 18(2), 288 – 303.Direktorat Pembinaan SMA. (2017). Panduan Penilaian oleh Pendidik dan Satuan Pendidikan Sekolah Menengah Atas. Jakarta: Kementerian Pendidikan dan Kebudayaan RI.Kohen, Z., Herscovitz, O., & Dori, Y. J. (2020). How to Promote Chemical Literacy? Online Question Posing And Communicating With Scientists. Chemistry Education Research And Practice, 21(1), 250 – 266Mudiono, A. (2016). Keprofesionalan Guru dalam Menghadapi Pendidikan di Era Global. Makalah disajikan dalam Seminar Nasional, Jurusan KSDP FIP UM, Malang 25 September.Mumba, F., & Hunter, W. J. F. (2009). Representative Nature of Scientific Literacy Themes in A High School Chemistry Course: The Case of Zambia. Chemistry Education Research And Practice, 10(3), 219 – 226.Naganuma, S. (2017). An Assessment of Civic Scientific Literacy in Japan: Development of A More Authentic Assessment Task And Scoring Rubric. International Journal of Science Education, Part B, 7(4), 301 – 322Norris, S. P., & Philip, L. M. (2003). How literacy in its fundamental sense in central to scientific literacy. Science Education, 87(2), 224 – 240.Organisation for Economic Co-operation and Development (OECD). (2016). PISA 2015 Assessment And Analytical Framework: Science, Reading, Mathematic And Financial Literacy. Paris: OECD PublishingOrganisation for Economic Co-operation and Development (OECD). (2018). PISA 2018 Result Combined Executive Summaries Volume I, II, & III. Paris: Organisation for Economic Co-operation and Development.Osborne, J. F. (2010). Arguing to Learn in Science: The Role of Collaborative, Critical Discourse. Science, 328(5977), 463 – 466Rahayu, S. (2014). Menuju Masyarakat Berliterasi Sains: Harapan dan Tantangan Kurikulum 2013. Makalah disajikan dalam Seminar Nasional Kimia dan Pembelajarannya, Jurusan Kimia FMIPA UM, Malang 6 September.Rahayu, S. (2017). Mengoptimalkan Aspek Literasi dalam Pembelajaran Kimia Abad 21. Makalah disajikan dalam Seminar Nasional Kimia, Jurusan Pendidikan Kimia FMIPA UNY, Yogyakarta, 14 Oktober.Riduwan. (2011). Belajar Mudah Penelitian: untuk Guru-Karyawan, dan Peneliti Pemula. Bandung: AlfabetaRiduwan. (2013). Dasar-Dasar Statistika. Bandung: AlfabetaShe, H. C., Stacey, K., & Schmidt, W. H. (2018).Science And Mathematics Literacy: PISA for Better School Education. International Journal of Science And Mathematics Education, 16(1), 1 – 5Shwartz, Y., Ben-Zvi, R., & Hofstein, A. (2005). The Importance of Involving High-School Chemistry Teachers in The Process of Defining the Operational Meaning of Chemical Literacy. International Journal of ScienceEducation, 27(3), 323 – 344.Thummathong, R., & Thathong, K. (2016). Construction of A Chemical Literacy Test for Engineering Students. Journal of Turkish Science Education, 13(3), 185 – 198.United Nations Environment Programme (UNEP). (2012). 21 Issues for the 21st Century: Result of the UNEP Foresight Process on Emerging Environmental Issues. Nairobi, Kenya: United Nations Environment Programme.Vogelzang, J., Admiraal, W. F., & van Driel, J. H. (2020). Effects of Scrum Methodology on Students' Critical Scientific Literacy: The Case of Green Chemistry. Chemistry Education Research And Practice, 21(3), 940 – 952.World Economic Forum (WEF). (2016). New Vision for Education: Fostering Social And Emotional Learning through Technology

Identifying and classifying attributes of packaging for customer satisfaction-A Kano Model Approach

[EN] The packaging industry in India is predicted to grow at 18% annually. In recent years Packaging becomes a potential marketing tool. The marketer should design the packaging of high quality from customer perspective.  As the research in the area of packaging is very few, study of quality attributes of Packaging is the need of the hour and inevitable. An empirical research was conducted by applying Kano Model. The researcher is interested to find out the perception of the customers on 22 quality attributes of packaging. 500 respondents which were selected randomly were asked about their experience of packing on everyday commodities through a well-structured questionnaire.  The classification of attribute as must-be quality, one-dimensional quality, attractive quality, indifferent quality and reverse quality was done by three methods. Marketer should make a note of it and prioritise the attributes for customer satisfaction.Dash, SK. (2021). Identifying and classifying attributes of packaging for customer satisfaction-A Kano Model Approach. International Journal of Production Management and Engineering. 9(1):57-64. https://doi.org/10.4995/ijpme.2021.13683OJS576491Bakhitar, A.,Hannan, A., Basit, A., Ahmad, J.(2015). Prioritization of value based services of software by using AHP and fuzzy KANO model. International Conference on Computational and Social Sciences, 8, 25- 27.Basfirinci, C., Mitra, A. (2015). A cross cultural investigation of airlines service quality through integration of Servqual and the Kano model. Journal of Air Transport Management, 42(1), 239-48. https://doi.org/10.1016/j.jairtraman.2014.11.005Berger, C., Blauth, R., Boger, D., Bolster, C., Burchill, G., DuMouchel, W., Pouliot, F., Richter, R., Rubinoff, A., Shen, D., Timko, M., Walden, D. (1993). Kano's methods for understanding customer-defined quality. The Center for Quality of Management Journal, 2(4), 2-36.Brown, G.H. (1950). Measuring consumer attitudes towards products. Journal of Marketing, 14(5), 691-98. https://doi.org/10.1177/002224295001400505Chaudha, A., Jain, R., Singh, A.R., Mishra, P.K. (2011). Integration of Kano's Model into Quality Function Deployment (QFD). Journal Advice Manufacture Technology, 53, 689-698. https://doi.org/10.1007/s00170-010-2867-0Cole, R.E. (2001). From continuous improvement to continuous innovation. Quality Management Journal, 8(4), 7-21. https://doi.org/10.1080/10686967.2001.11918977Dash, S.K. (2019). Application of Kano Model in Identifying Attributes. A Case Study on School Bus Services. International Journal of Management Studies, 6(1), 31-37. https://doi.org/10.18843/ijms/v6i1(3)/03Dziuba, S.T., Śron, B. (2014). FAM-FMC system as an alternative element of the software used in a grain and flour milling enterprise. Production Engineering Archives, 4(3),29-31. https://doi.org/10.30657/pea.2014.04.08Ernzer, M., Kopp, K.(2003). Application of KANO method to life cycle design. IEEE Proceedings of Eco Design: Third International Symposium on Environmentally Conscious De-sign and Inverse Manufacturing, Tokyo Japan, December 8-11, 383-389. https://doi.org/10.1109/ECODIM.2003.1322697Feigenbaum, A.V. (1991).Total Quality Control. McGraw-Hill. Fundin, A., Nilsson, L. (2003). Using Kano's theory of attractive quality to better understand customer satisfaction with e-services. Asian Journal on Quality, 4(2), 32-49. https://doi.org/10.1108/15982688200300018Friman, M., Edvardsson, B. (2003). A content analysis of complaints and compliments. Managing Service Quality, 13(1), 20-26. https://doi.org/10.1108/09604520310456681Garvin, D.A. (1987). Competing on the eight dimensions of quality. Harvard Business Review, 65(6), 101-109.Hanan, M., Karp, P. (1989). Customer satisfaction, how to maximise, measure and market your company's "ultimate product". AMACOM.Herzberg, F., Bernard, M., Snyderman, B.B. (1959). The Motivation to Work. John Wiley and Sons.Hoch, S.J., Ha, Y.W. (1986). Consumer learning: advertising and the ambiguity of product experience. Journal of Consumer Research, 13, 221-33.https://doi.org/10.1086/209062Johnson, M.D., Nilsson, L. (2003). The Importance of Reliability and Customization from Goods to Services. Quality Management Journal, 10(1), 8-19. https://doi.org/10.1080/10686967.2003.11919049Kano, N., Seraku, N., Takahashi, F., Tsuji, S. (1984). Attractive Quality and Must-Be Quality. Journal of the Japanese Society for Quality Control, 41, 39-48.Kapalle, P.K, Lehmann, D.R. (1995). The effects of advertised and observed quality on expectations about new product quality. Journal of Marketing Research, 32(8), 280-90. https://doi.org/10.1177/002224379503200304Lee, M.C., Newcomb, J.F. (1997). Applying the Kano methodology to meet customer requirements: NASA's microgravity science program. Quality Management Journal, 4(3), 95-110. https://doi.org/10.1080/10686967.1997.11918805Löfgren, M. (2005). Winning at the first and second moments of truth: An exploratory study. Journal of Service Theory and Practice, 15(1), 102-15. https://doi.org/10.1108/09604520510575290Löfgren, M., Witell, L. (2005). Kano's Theory of Attractive Quality and Packaging. Quality Management Journal, 12(3), 7-20. https://doi.org/10.1080/10686967.2005.11919257Matzler, K., Hinterhuber, H.H., Bailom, F., Sauerwein, E. (1996). How to delight your customers. Journal of Product & Brand Management, 5(2), 6-18. https://doi.org/10.1108/10610429610119469Miarka, D., Żukowska, J., Siwek, A., Nowacka,A., Nowak, D. (2015). Microbial hazards reduction during creamy cream cheese production. Production Engineering Archives, 6(1), 39-44. https://doi.org/10.30657/pea.2015.06.10Nelson, P. (1970), Information and consumer behaviour. Journal of Political Economy, 78, 311-29. https://doi.org/10.1086/259630Nilsson-Witell, L, Fundin, A. (2005). Dynamics of service attributes: a test of Kano's theory of attractive quality. International Journal of Service Industry Management, 16(2), 152-168. https://doi.org/10.1108/09564230510592289Parasuraman, A. (1997). Reflections on gaining competitive advantage through customer value. Academy of Marketing Science Journal, 25(2), 154-61. https://doi.org/10.1007/BF02894351Parasuraman, A., Colby, C.L. (2001). Techno-Ready Marketing. Free Press.Qiting, P., Uno, N., Kubota, Y. (2013). Kano Model Analysis of Customer Needs and Satisfaction at the Shanghai Disneyland. In Proceedings of the 5th Intl Congress of the Intl Association of Societies of Design Research, Tokyo, Japan. http://design-cu.jp/iasdr2013/papers/1835-1b.pdf Accessed on January 2021.Sauerwein, E., Bailom, F., Matzler, K., Hinterhuber, H.H. (1996). The Kano Model: How to delight your Customers. Volume I of the IX. International Working Seminar on Production Economics, Innsbruck/Igls/Austria, February 19-23 1996, pp. 313-327. https://is.muni. cz/el/econ/podzim2009/MPH_MAR2/um/9899067/THE_KANO_MODEL_-_HOW_TO_DELIGHT_YOUR_CUSTOMERS.pdfShewhart, W.A. (1931). Economic Control of Quality of Manufactured Product. D. Van Nostrand Company, Inc.Underwood, R.L., Klein, N.M. (2002). Packaging as Brand Communication: Effects of Product Pictures on Consumer Responses to the Package and Brand. Journal of Marketing Theory and Practice, 10(4), 58-68. https://doi.org/10.1080/10696679.2002.11501926Underwood, R.L. Klein, N.M., Burke, R.R. (2001). Packaging communication: attentional effects of product imagery. Journal of Product & Brand Management, 10(7), 403-22. https://doi.org/10.1108/10610420110410531Watson, G.H. (2003), "Customer focus and competitiveness", in Stephens, K.S. (Ed.), Six Sigma and Related Studies in the Quality Disciplines, ASQ Quality Press, Milwaukee, WI.Williams, D. (2020). 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Analysis of the Flow in a Typified USBR II Stilling Basin through a Numerical and Physical Modeling Approach

[EN] Adaptation of stilling basins to higher discharges than those considered for their design implies deep knowledge of the flow developed in these structures. To this end, the hydraulic jump occurring in a typified United States Bureau of Reclamation Type II (USBR II) stilling basin was analyzed using a numerical and experimental modeling approach. A reduced-scale physical model to conduct an experimental campaign was built and a numerical computational fluid dynamics (CFD) model was prepared to carry out the corresponding simulations. Both models were able to successfully reproduce the case study in terms of hydraulic jump shape, velocity profiles, and pressure distributions. The analysis revealed not only similarities to the flow in classical hydraulic jumps but also the influence of the energy dissipation devices existing in the stilling basin, all in good agreement with bibliographical information, despite some slight differences. Furthermore, the void fraction distribution was analyzed, showing satisfactory performance of the physical model, although the numerical approach presented some limitations to adequately represent the flow aeration mechanisms, which are discussed herein. Overall, the presented modeling approach can be considered as a useful tool to address the analysis of free surface flows occurring in stilling basins.This research was funded by 'Generalitat Valenciana predoctoral grants (Grant number [2015/7521])', in collaboration with the European Social Funds and by the research project: 'La aireacion del flujo y su implementacion en prototipo para la mejora de la disipacion de energia de la lamina vertiente por resalto hidraulico en distintos tipos de presas' (BIA2017-85412-C2-1-R), funded by the Spanish Ministry of Economy.Macián Pérez, JF.; García-Bartual, R.; Huber, B.; Bayón, A.; Vallés-Morán, FJ. (2020). Analysis of the Flow in a Typified USBR II Stilling Basin through a Numerical and Physical Modeling Approach. Water. 12(1):1-20. https://doi.org/10.3390/w12010227S120121Bayon, A., Valero, D., García-Bartual, R., Vallés-Morán, F. ​José, & López-Jiménez, P. A. (2016). Performance assessment of OpenFOAM and FLOW-3D in the numerical modeling of a low Reynolds number hydraulic jump. Environmental Modelling & Software, 80, 322-335. doi:10.1016/j.envsoft.2016.02.018Chanson, H. (2008). Turbulent air–water flows in hydraulic structures: dynamic similarity and scale effects. Environmental Fluid Mechanics, 9(2), 125-142. doi:10.1007/s10652-008-9078-3Heller, V. (2011). Scale effects in physical hydraulic engineering models. Journal of Hydraulic Research, 49(3), 293-306. doi:10.1080/00221686.2011.578914Chanson, H. (2013). Hydraulics of aerated flows:qui pro quo? Journal of Hydraulic Research, 51(3), 223-243. doi:10.1080/00221686.2013.795917Blocken, B., & Gualtieri, C. (2012). Ten iterative steps for model development and evaluation applied to Computational Fluid Dynamics for Environmental Fluid Mechanics. Environmental Modelling & Software, 33, 1-22. doi:10.1016/j.envsoft.2012.02.001Wang, H., & Chanson, H. (2015). Experimental Study of Turbulent Fluctuations in Hydraulic Jumps. Journal of Hydraulic Engineering, 141(7), 04015010. doi:10.1061/(asce)hy.1943-7900.0001010Valero, D., Viti, N., & Gualtieri, C. (2018). Numerical Simulation of Hydraulic Jumps. Part 1: Experimental Data for Modelling Performance Assessment. Water, 11(1), 36. doi:10.3390/w11010036Viti, N., Valero, D., & Gualtieri, C. (2018). Numerical Simulation of Hydraulic Jumps. Part 2: Recent Results and Future Outlook. Water, 11(1), 28. doi:10.3390/w11010028Bayon-Barrachina, A., & Lopez-Jimenez, P. A. (2015). Numerical analysis of hydraulic jumps using OpenFOAM. Journal of Hydroinformatics, 17(4), 662-678. doi:10.2166/hydro.2015.041Teuber, K., Broecker, T., Bayón, A., Nützmann, G., & Hinkelmann, R. (2019). CFD-modelling of free surface flows in closed conduits. Progress in Computational Fluid Dynamics, An International Journal, 19(6), 368. doi:10.1504/pcfd.2019.103266Chachereau, Y., & Chanson, H. (2011). Free-surface fluctuations and turbulence in hydraulic jumps. Experimental Thermal and Fluid Science, 35(6), 896-909. doi:10.1016/j.expthermflusci.2011.01.009Zhang, G., Wang, H., & Chanson, H. (2012). Turbulence and aeration in hydraulic jumps: free-surface fluctuation and integral turbulent scale measurements. Environmental Fluid Mechanics, 13(2), 189-204. doi:10.1007/s10652-012-9254-3Mossa, M. (1999). On the oscillating characteristics of hydraulic jumps. Journal of Hydraulic Research, 37(4), 541-558. doi:10.1080/00221686.1999.9628267Chanson, H., & Brattberg, T. (2000). Experimental study of the air–water shear flow in a hydraulic jump. International Journal of Multiphase Flow, 26(4), 583-607. doi:10.1016/s0301-9322(99)00016-6Murzyn, F., Mouaze, D., & Chaplin, J. R. (2005). Optical fibre probe measurements of bubbly flow in hydraulic jumps. International Journal of Multiphase Flow, 31(1), 141-154. doi:10.1016/j.ijmultiphaseflow.2004.09.004Gualtieri, C., & Chanson, H. (2007). Experimental analysis of Froude number effect on air entrainment in the hydraulic jump. Environmental Fluid Mechanics, 7(3), 217-238. doi:10.1007/s10652-006-9016-1Chanson, H., & Gualtieri, C. (2008). Similitude and scale effects of air entrainment in hydraulic jumps. Journal of Hydraulic Research, 46(1), 35-44. doi:10.1080/00221686.2008.9521841Ho, D. K. H., & Riddette, K. M. (2010). Application of computational fluid dynamics to evaluate hydraulic performance of spillways in australia. Australian Journal of Civil Engineering, 6(1), 81-104. doi:10.1080/14488353.2010.11463946Dong, Wang, Vetsch, Boes, & Tan. (2019). Numerical Simulation of Air–Water Two-Phase Flow on Stepped Spillways Behind X-Shaped Flaring Gate Piers under Very High Unit Discharge. Water, 11(10), 1956. doi:10.3390/w11101956Toso, J. W., & Bowers, C. E. (1988). Extreme Pressures in Hydraulic‐Jump Stilling Basins. Journal of Hydraulic Engineering, 114(8), 829-843. doi:10.1061/(asce)0733-9429(1988)114:8(829)Houichi, L., Ibrahim, G., & Achour, B. (2006). Experiments for the Discharge Capacity of the Siphon Spillway Having the Creager-Ofitserov Profile. International Journal of Fluid Mechanics Research, 33(5), 395-406. doi:10.1615/interjfluidmechres.v33.i5.10Padulano, R., Fecarotta, O., Del Giudice, G., & Carravetta, A. (2017). Hydraulic Design of a USBR Type II Stilling Basin. Journal of Irrigation and Drainage Engineering, 143(5), 04017001. doi:10.1061/(asce)ir.1943-4774.0001150Hirt, C. ., & Nichols, B. . (1981). Volume of fluid (VOF) method for the dynamics of free boundaries. 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Physics of Fluids A: Fluid Dynamics, 4(7), 1510-1520. doi:10.1063/1.858424Li, S., & Zhang, J. (2018). Numerical Investigation on the Hydraulic Properties of the Skimming Flow over Pooled Stepped Spillway. Water, 10(10), 1478. doi:10.3390/w10101478Zhang, W., Wang, J., Zhou, C., Dong, Z., & Zhou, Z. (2018). Numerical Simulation of Hydraulic Characteristics in A Vortex Drop Shaft. Water, 10(10), 1393. doi:10.3390/w10101393Xiang, M., Cheung, S. C. P., Tu, J. Y., & Zhang, W. H. (2014). A multi-fluid modelling approach for the air entrainment and internal bubbly flow region in hydraulic jumps. Ocean Engineering, 91, 51-63. doi:10.1016/j.oceaneng.2014.08.016Procedure for Estimation and Reporting of Uncertainty Due to Discretization in CFD Applications. (2008). Journal of Fluids Engineering, 130(7), 078001. doi:10.1115/1.2960953Cartellier, A., & Achard, J. L. (1991). Local phase detection probes in fluid/fluid two‐phase flows. Review of Scientific Instruments, 62(2), 279-303. doi:10.1063/1.1142117Cartellier, A., & Barrau, E. (1998). Monofiber optical probes for gas detection and gas velocity measurements: conical probes. International Journal of Multiphase Flow, 24(8), 1265-1294. doi:10.1016/s0301-9322(98)00032-9Boyer, C., Duquenne, A.-M., & Wild, G. (2002). Measuring techniques in gas–liquid and gas–liquid–solid reactors. Chemical Engineering Science, 57(16), 3185-3215. doi:10.1016/s0009-2509(02)00193-8Hager, W. H., & Bremen, R. (1989). Classical hydraulic jump: sequent depths. Journal of Hydraulic Research, 27(5), 565-585. doi:10.1080/00221688909499111Hager, W. H., & Li, D. (1992). Sill-controlled energy dissipator. Journal of Hydraulic Research, 30(2), 165-181. doi:10.1080/00221689209498932Bakhmeteff, B. A., & Matzke, A. E. (1936). The Hydraulic Jump in Terms of Dynamic Similarity. Transactions of the American Society of Civil Engineers, 101(1), 630-647. doi:10.1061/taceat.0004708Hager, W. 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Evaluation of Bipolar, Tripolar, and Quadripolar Laplacian Estimates of Electrocardiogram via Concentric Ring Electrodes

[EN] Surface Laplacian estimates via concentric ring electrodes (CREs) have proven to enhance spatial resolution compared to conventional disc electrodes, which is of great importance for P-wave analysis. In this study, Laplacian estimates for traditional bipolar configuration (BC), two tripolar configurations with linearly decreasing and increasing inter-ring distances (TCLDIRD and TCLIIRD, respectively), and quadripolar configuration (QC) were obtained from cardiac recordings with pentapolar CREs placed at CMV1 and CMV2 positions. Normalized P-wave amplitude (NAP) was computed to assess the contrast to study atrial activity. Signals were of good quality (20-30 dB). Atrial activity was more emphasized at CMV1 (NAP similar or equal to 0.19-0.24) compared to CMV2 (NAP similar or equal to 0.08-0.10). Enhanced spatial resolution of TCLIIRD and QC resulted in higher NAP values than BC and TCLDIRD. Comparison with simultaneous standard 12-lead ECG proved that Laplacian estimates at CMV1 outperformed all the limb and chest standard leads in the contrast to study P-waves. Clinical recordings with CRE at this position could allow more detailed observation of atrial activity and facilitate the diagnosis of associated pathologies. Furthermore, such recordings would not require additional electrodes on limbs and could be performed wirelessly, so it should also be suitable for ambulatory monitoring, for example, using cardiac Holter monitors.This research was funded by the National Science Foundation (NSF) Division of Human Resource Development (HRD) Tribal Colleges and Universities Program (TCUP), grants number 1622481 and 1914787 to O.M.Garcia-Casado, J.; Ye Lin, Y.; Prats-Boluda, G.; Makeyev, O. (2019). Evaluation of Bipolar, Tripolar, and Quadripolar Laplacian Estimates of Electrocardiogram via Concentric Ring Electrodes. Sensors. 19(17):1-11. https://doi.org/10.3390/s19173780S1111917Roth, G. A., Johnson, C., Abajobir, A., Abd-Allah, F., Abera, S. F., Abyu, G., … Alam, K. (2017). Global, Regional, and National Burden of Cardiovascular Diseases for 10 Causes, 1990 to 2015. Journal of the American College of Cardiology, 70(1), 1-25. doi:10.1016/j.jacc.2017.04.052Lopez, A. D., Mathers, C. D., Ezzati, M., Jamison, D. T., & Murray, C. J. (2006). Global and regional burden of disease and risk factors, 2001: systematic analysis of population health data. The Lancet, 367(9524), 1747-1757. doi:10.1016/s0140-6736(06)68770-9Bhatnagar, P., Wickramasinghe, K., Wilkins, E., & Townsend, N. (2016). Trends in the epidemiology of cardiovascular disease in the UK. Heart, 102(24), 1945-1952. doi:10.1136/heartjnl-2016-309573https://healthmetrics.heart.org/cardiovascular-disease-a-costly-burden/Leal, J., Luengo-Fernández, R., Gray, A., Petersen, S., & Rayner, M. (2006). Economic burden of cardiovascular diseases in the enlarged European Union. European Heart Journal, 27(13), 1610-1619. doi:10.1093/eurheartj/ehi733Wang, Y., Cuculich, P. S., Zhang, J., Desouza, K. A., Vijayakumar, R., Chen, J., … Rudy, Y. (2011). Noninvasive Electroanatomic Mapping of Human Ventricular Arrhythmias with Electrocardiographic Imaging. Science Translational Medicine, 3(98), 98ra84-98ra84. doi:10.1126/scitranslmed.3002152SippensGroenewegen, A., Peeters, H. A. P., Jessurun, E. R., Linnenbank, A. C., Robles de Medina, E. O., Lesh, M. D., & van Hemel, N. M. (1998). Body Surface Mapping During Pacing at Multiple Sites in the Human Atrium. Circulation, 97(4), 369-380. doi:10.1161/01.cir.97.4.369Kornreich, F., MacLeod, R. S., & Lux, R. L. (2008). Supplemented standard 12-lead electrocardiogram for optimal diagnosis and reconstruction of significant body surface map patterns. Journal of Electrocardiology, 41(3), 251-256. doi:10.1016/j.jelectrocard.2008.02.011Fereniec, M., Stix, G., Kania, M., Mroczka, T., & Maniewski, R. (2013). An Analysis of the U-Wave and Its Relation to the T-Wave in Body Surface Potential Maps for Healthy Subjects and MI Patients. Annals of Noninvasive Electrocardiology, 19(2), 145-156. doi:10.1111/anec.12110Lian, J., Li, G., Cheng, J., Avitall, B., & He, B. (2002). Body surface Laplacian mapping of atrial depolarization in healthy human subjects. Medical & Biological Engineering & Computing, 40(6), 650-659. doi:10.1007/bf02345304Wu, D., Tsai, H. C., & He, B. (1999). On the Estimation of the Laplacian Electrocardiogram during Ventricular Activation. Annals of Biomedical Engineering, 27(6), 731-745. doi:10.1114/1.224He, B., & Cohen, R. J. (1992). Body surface Laplacian mapping of cardiac electrical activity. The American Journal of Cardiology, 70(20), 1617-1620. doi:10.1016/0002-9149(92)90471-aHe, B., & Cohen, R. J. (1992). Body surface Laplacian ECG mapping. IEEE Transactions on Biomedical Engineering, 39(11), 1179-1191. doi:10.1109/10.168684He, B., & Cohen, R. J. (1995). Body Surface Laplacian Electrocardiographic Mapping−A Review. Critical Reviews in Biomedical Engineering, 23(5-6), 475-510. doi:10.1615/critrevbiomedeng.v23.i5-6.30UMETANI, K., OKAMOTO, Y., MASHIMA, S., ONO, K., HOSAKA, H., & HE, B. (1998). Body Surface Laplacian Mapping in Patients with Left or Right Ventricular Bundle Branch Block. Pacing and Clinical Electrophysiology, 21(11), 2043-2054. doi:10.1111/j.1540-8159.1998.tb01122.xBin He, Guanglin Li, & Jie Lian. (2002). A spline Laplacian ECG estimator in a realistic geometry volume conductor. IEEE Transactions on Biomedical Engineering, 49(2), 110-117. doi:10.1109/10.979350Besio, G., Koka, K., Aakula, R., & Weizhong Dai. (2006). Tri-polar concentric ring electrode development for Laplacian electroencephalography. IEEE Transactions on Biomedical Engineering, 53(5), 926-933. doi:10.1109/tbme.2005.863887Besio, W., Aakula, R., Koka, K., & Dai, W. (2006). Development of a Tri-polar Concentric Ring Electrode for Acquiring Accurate Laplacian Body Surface Potentials. Annals of Biomedical Engineering, 34(3), 426-435. doi:10.1007/s10439-005-9054-8Besio, W., & Chen, T. (2007). Tripolar Laplacian electrocardiogram and moment of activation isochronal mapping. Physiological Measurement, 28(5), 515-529. doi:10.1088/0967-3334/28/5/006Prats-Boluda, G., Garcia-Casado, J., Martinez-de-Juan, J. L., & Ye-Lin, Y. (2011). Active concentric ring electrode for non-invasive detection of intestinal myoelectric signals. Medical Engineering & Physics, 33(4), 446-455. doi:10.1016/j.medengphy.2010.11.009Prats-Boluda, G., Ye-Lin, Y., Bueno-Barrachina, J., Rodriguez de Sanabria, R., & Garcia-Casado, J. (2016). Towards the clinical use of concentric electrodes in ECG recordings: influence of ring dimensions and electrode position. Measurement Science and Technology, 27(2), 025705. doi:10.1088/0957-0233/27/2/025705Zena-Giménez, V., Garcia-Casado, J., Ye-Lin, Y., Garcia-Breijo, E., & Prats-Boluda, G. (2018). A Flexible Multiring Concentric Electrode for Non-Invasive Identification of Intestinal Slow Waves. Sensors, 18(2), 396. doi:10.3390/s18020396Ye-Lin, Y., Alberola-Rubio, J., Prats-boluda, G., Perales, A., Desantes, D., & Garcia-Casado, J. (2014). Feasibility and Analysis of Bipolar Concentric Recording of Electrohysterogram with Flexible Active Electrode. Annals of Biomedical Engineering, 43(4), 968-976. doi:10.1007/s10439-014-1130-5Wang, K., Parekh, U., Pailla, T., Garudadri, H., Gilja, V., & Ng, T. N. (2017). Stretchable Dry Electrodes with Concentric Ring Geometry for Enhancing Spatial Resolution in Electrophysiology. Advanced Healthcare Materials, 6(19), 1700552. doi:10.1002/adhm.201700552Lidón-Roger, J., Prats-Boluda, G., Ye-Lin, Y., Garcia-Casado, J., & Garcia-Breijo, E. (2018). Textile Concentric Ring Electrodes for ECG Recording Based on Screen-Printing Technology. Sensors, 18(1), 300. doi:10.3390/s18010300Makeyev, O., Ding, Q., & Besio, W. G. (2016). Improving the accuracy of Laplacian estimation with novel multipolar concentric ring electrodes. Measurement, 80, 44-52. doi:10.1016/j.measurement.2015.11.017Makeyev, O., & Besio, W. (2016). Improving the Accuracy of Laplacian Estimation with Novel Variable Inter-Ring Distances Concentric Ring Electrodes. Sensors, 16(6), 858. doi:10.3390/s16060858Makeyev, O. (2018). Solving the general inter-ring distances optimization problem for concentric ring electrodes to improve Laplacian estimation. BioMedical Engineering OnLine, 17(1). doi:10.1186/s12938-018-0549-6Ye-Lin, Y., Bueno-Barrachina, J. M., Prats-boluda, G., Rodriguez de Sanabria, R., & Garcia-Casado, J. (2017). Wireless sensor node for non-invasive high precision electrocardiographic signal acquisition based on a multi-ring electrode. Measurement, 97, 195-202. doi:10.1016/j.measurement.2016.11.009Prats-Boluda, G., Ye-Lin, Y., Pradas-Novella, F., Garcia-Breijo, E., & Garcia-Casado, J. (2018). Textile Concentric Ring Electrodes: Influence of Position and Electrode Size on Cardiac Activity Monitoring. Journal of Sensors, 2018, 1-9. doi:10.1155/2018/7290867Huiskamp, G. (1991). Difference formulas for the surface Laplacian on a triangulated surface. Journal of Computational Physics, 95(2), 477-496. doi:10.1016/0021-9991(91)90286-tHamilton, P. S., & Tompkins, W. J. (1986). Quantitative Investigation of QRS Detection Rules Using the MIT/BIH Arrhythmia Database. IEEE Transactions on Biomedical Engineering, BME-33(12), 1157-1165. doi:10.1109/tbme.1986.325695Koka, K., & Besio, W. G. (2007). Improvement of spatial selectivity and decrease of mutual information of tri-polar concentric ring electrodes. Journal of Neuroscience Methods, 165(2), 216-222. doi:10.1016/j.jneumeth.2007.06.007Prats-Boluda, G., Ye-Lin, Y., Bueno Barrachina, J. M., Senent, E., Rodriguez de Sanabria, R., & Garcia-Casado, J. (2015). Development of a portable wireless system for bipolar concentric ECG recording. Measurement Science and Technology, 26(7), 075102. doi:10.1088/0957-0233/26/7/07510

Improving Distributed Decision Making in Inventory Management: A Combined ABC-AHP Approach Supported by Teamwork

[EN] The need of organizations to ensure service levels that impact on customer satisfaction has required the design of collaborative processes among stakeholders involved in inventory decision making. The increase of quantity and variety of items, on the one hand, and demand and customer expectations, on the other hand, are transformed into a greater complexity in inventory management, requiring effective communication and agreements between the leaders of the logistics processes. Traditionally, decision making in inventory management was based on approaches conditioned only by cost or sales volume. These approaches must be overcome by others that consider multiple criteria, involving several areas of the companies and taking into account the opinions of the stakeholders involved in these decisions. Inventory management becomes part of a complex system that involves stakeholders from different areas of the company, where each agent has limited information and where the cooperation between such agents is key for the system's performance. In this paper, a distributed inventory control approach was used with the decisions allowing communication between the stakeholders and with a multicriteria group decision-making perspective. This work proposes a methodology that combines the analysis of the value chain and the AHP technique, in order to improve communication and the performance of the areas related to inventory management decision making. This methodology uses the areas of the value chain as a theoretical framework to identify the criteria necessary for the application of the AHP multicriteria group decision-making technique. These criteria were defined as indicators that measure the performance of the areas of the value chain related to inventory management and were used to classify ABC inventory of the products according to these selected criteria. Therefore, the methodology allows us to solve inventory management DDM based on multicriteria ABC classification and was validated in a Colombian company belonging to the graphic arts sector.Pérez Vergara, IG.; Arias Sánchez, JA.; Poveda Bautista, R.; Diego-Mas, JA. (2020). Improving Distributed Decision Making in Inventory Management: A Combined ABC-AHP Approach Supported by Teamwork. Complexity. 2020:1-13. https://doi.org/10.1155/2020/6758108S1132020Poveda-Bautista, R., Baptista, D. C., & García-Melón, M. (2012). Setting competitiveness indicators using BSC and ANP. International Journal of Production Research, 50(17), 4738-4752. doi:10.1080/00207543.2012.657964Castro Zuluaga, C. A., Velez Gallego, M. C., & Catro Urrego, J. A. (2011). Clasificación ABC Multicriterio: Tipos de Criterios y efectos en la asignación de pesos. ITECKNE, 8(2). doi:10.15332/iteckne.v8i2.35Morash, E. A., & Clinton, S. R. (1998). Supply Chain Integration: Customer Value through Collaborative Closeness versus Operational Excellence. Journal of Marketing Theory and Practice, 6(4), 104-120. doi:10.1080/10696679.1998.11501814Fabbe-Costes, N. (2015). Évaluer la création de valeurdu Supply Chain Management. Logistique & Management, 23(4), 41-50. doi:10.1080/12507970.2015.11758621Flores, B. E., & Clay Whybark, D. (1986). Multiple Criteria ABC Analysis. International Journal of Operations & Production Management, 6(3), 38-46. doi:10.1108/eb054765Partovi, F. Y., & Burton, J. (1993). Using the Analytic Hierarchy Process for ABC Analysis. International Journal of Operations & Production Management, 13(9), 29-44. doi:10.1108/01443579310043619Balaji, K., & Kumar, V. S. S. (2014). Multicriteria Inventory ABC Classification in an Automobile Rubber Components Manufacturing Industry. Procedia CIRP, 17, 463-468. doi:10.1016/j.procir.2014.02.044Ramanathan, R. (2006). ABC inventory classification with multiple-criteria using weighted linear optimization. Computers & Operations Research, 33(3), 695-700. doi:10.1016/j.cor.2004.07.014Van Kampen, T. J., Akkerman, R., & Pieter van Donk, D. (2012). SKU classification: a literature review and conceptual framework. International Journal of Operations & Production Management, 32(7), 850-876. doi:10.1108/01443571211250112Flores, B. E., Olson, D. L., & Dorai, V. K. (1992). Management of multicriteria inventory classification. Mathematical and Computer Modelling, 16(12), 71-82. doi:10.1016/0895-7177(92)90021-cGajpal, P. P., Ganesh, L. S., & Rajendran, C. (1994). Criticality analysis of spare parts using the analytic hierarchy process. International Journal of Production Economics, 35(1-3), 293-297. doi:10.1016/0925-5273(94)90095-7Scala, N. M., Rajgopal, J., & Needy, K. L. (2014). Managing Nuclear Spare Parts Inventories: A Data Driven Methodology. IEEE Transactions on Engineering Management, 61(1), 28-37. doi:10.1109/tem.2013.2283170Hadad, Y., & Keren, B. (2013). ABC inventory classification via linear discriminant analysis and ranking methods. International Journal of Logistics Systems and Management, 14(4), 387. doi:10.1504/ijlsm.2013.052744Altay Guvenir, H., & Erel, E. (1998). Multicriteria inventory classification using a genetic algorithm. European Journal of Operational Research, 105(1), 29-37. doi:10.1016/s0377-2217(97)00039-8Rezaei, J., & Dowlatshahi, S. (2010). A rule-based multi-criteria approach to inventory classification. International Journal of Production Research, 48(23), 7107-7126. doi:10.1080/00207540903348361Hatefi, S. M., Torabi, S. A., & Bagheri, P. (2013). Multi-criteria ABC inventory classification with mixed quantitative and qualitative criteria. International Journal of Production Research, 52(3), 776-786. doi:10.1080/00207543.2013.838328Ishizaka, A., Pearman, C., & Nemery, P. (2012). AHPSort: an AHP-based method for sorting problems. International Journal of Production Research, 50(17), 4767-4784. doi:10.1080/00207543.2012.657966Yu, M.-C. (2011). Multi-criteria ABC analysis using artificial-intelligence-based classification techniques. Expert Systems with Applications, 38(4), 3416-3421. doi:10.1016/j.eswa.2010.08.127Tsai, C.-Y., & Yeh, S.-W. (2008). A multiple objective particle swarm optimization approach for inventory classification. International Journal of Production Economics, 114(2), 656-666. doi:10.1016/j.ijpe.2008.02.017Aydin Keskin, G., & Ozkan, C. (2013). Multiple Criteria ABC Analysis with FCM Clustering. Journal of Industrial Engineering, 2013, 1-7. doi:10.1155/2013/827274Lolli, F., Ishizaka, A., & Gamberini, R. (2014). New AHP-based approaches for multi-criteria inventory classification. International Journal of Production Economics, 156, 62-74. doi:10.1016/j.ijpe.2014.05.015Raja, A. M. L., Ai, T. J., & Astanti, R. D. (2016). A Clustering Classification of Spare Parts for Improving Inventory Policies. IOP Conference Series: Materials Science and Engineering, 114, 012075. doi:10.1088/1757-899x/114/1/012075Zowid, F. M., Babai, M. Z., Douissa, M. R., & Ducq, Y. (2019). Multi-criteria inventory ABC classification using Gaussian Mixture Model. IFAC-PapersOnLine, 52(13), 1925-1930. doi:10.1016/j.ifacol.2019.11.484Babai, M. Z., Ladhari, T., & Lajili, I. (2014). On the inventory performance of multi-criteria classification methods: empirical investigation. International Journal of Production Research, 53(1), 279-290. doi:10.1080/00207543.2014.952791Schneeweiss, C. (2003). Distributed decision making––a unified approach. European Journal of Operational Research, 150(2), 237-252. doi:10.1016/s0377-2217(02)00501-5Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83. doi:10.1504/ijssci.2008.017590Cakir, O., & Canbolat, M. S. (2008). A web-based decision support system for multi-criteria inventory classification using fuzzy AHP methodology. Expert Systems with Applications, 35(3), 1367-1378. doi:10.1016/j.eswa.2007.08.041Liu, J., Liao, X., Zhao, W., & Yang, N. (2016). A classification approach based on the outranking model for multiple criteria ABC analysis. Omega, 61, 19-34. doi:10.1016/j.omega.2015.07.004Douissa, M. R., & Jabeur, K. (2016). A New Model for Multi-criteria ABC Inventory Classification: PROAFTN Method. Procedia Computer Science, 96, 550-559. doi:10.1016/j.procs.2016.08.233Lolli, F., Balugani, E., Ishizaka, A., Gamberini, R., Rimini, B., & Regattieri, A. (2018). Machine learning for multi-criteria inventory classification applied to intermittent demand. Production Planning & Control, 30(1), 76-89. doi:10.1080/09537287.2018.1525506Kartal, H., Oztekin, A., Gunasekaran, A., & Cebi, F. (2016). An integrated decision analytic framework of machine learning with multi-criteria decision making for multi-attribute inventory classification. Computers & Industrial Engineering, 101, 599-613. doi:10.1016/j.cie.2016.06.004López-Soto, D., Angel-Bello, F., Yacout, S., & Alvarez, A. (2017). A multi-start algorithm to design a multi-class classifier for a multi-criteria ABC inventory classification problem. Expert Systems with Applications, 81, 12-21. doi:10.1016/j.eswa.2017.02.048Dweiri, F., Kumar, S., Khan, S. A., & Jain, V. (2016). Designing an integrated AHP based decision support system for supplier selection in automotive industry. Expert Systems with Applications, 62, 273-283. doi:10.1016/j.eswa.2016.06.030Bruno, G., Esposito, E., Genovese, A., & Simpson, M. (2016). Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment. Expert Systems with Applications, 43, 271-285. doi:10.1016/j.eswa.2015.07.016Poza, C. (2020). A Conceptual Model to Measure Football Player’s Market Value. A Proposal by means of an Analytic Hierarchy Process. [Un modelo conceptual para medir el valor de mercado de los futbolistas. Una propuesta a través de un proceso analítico jerárquico]. RICYDE. Revista internacional de ciencias del deporte, 16(59), 24-42. doi:10.5232/ricyde2020.05903Guarnieri, P., Sobreiro, V. A., Nagano, M. S., & Marques Serrano, A. L. (2015). The challenge of selecting and evaluating third-party reverse logistics providers in a multicriteria perspective: a Brazilian case. Journal of Cleaner Production, 96, 209-219. doi:10.1016/j.jclepro.2014.05.040Ishizaka, A., & Labib, A. (2011). Selection of new production facilities with the Group Analytic Hierarchy Process Ordering method. Expert Systems with Applications, 38(6), 7317-7325. doi:10.1016/j.eswa.2010.12.004Partovi, F. Y., & Anandarajan, M. (2002). Classifying inventory using an artificial neural network approach. Computers & Industrial Engineering, 41(4), 389-404. doi:10.1016/s0360-8352(01)00064-xAlonso-Manzanedo, M., De-la -Fuente-Aragon, M. V., & Ros-McDonnell, L. (2013). A Proposed Collaborative Network Enterprise Model in the Fruit-and-Vegetable Sector Using Maturity Models. Annals of Industrial Engineering 2012, 359-366. doi:10.1007/978-1-4471-5349-8_42Augusto, M., Lisboa, J., Yasin, M., & Figueira, J. R. (2008). Benchmarking in a multiple criteria performance context: An application and a conceptual framework. 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Stochastic inverse finite element modeling for characterization of heterogeneous material properties

[EN] The micro and meso-structural characteristics of materials present an inherent variability because of the intrinsic scatter in raw material and manufacturing processes. This problem is exacerbated in highly heterogeneous materials, which shows significant uncertainties in the macroscale material properties. Therefore, providing optimal designs and reliable structural analyses strongly depend on the selection of the underlying material property models. This paper is intended to provide insight into such a dependence by means of a stochastic inverse model based on an iterative optimization process depending only of one parameter, thus avoiding complex parametrizations. It relies on nonlinear combinations of material property realizations with a defined spatial structure for constraining stochastic simulations to data within the framework of a Finite Element approach. In this way, the procedure gradually deforms unconditional material property realizations to approximate the reproduction of information including mechanical parameters (such as Young's modulus and Poisson's ratio fields) and variables (e.g., stress and strain fields). It allows dealing with non-multiGaussian structures for the spatial structure of the material property realizations, thus allowing to reproduce the coalescence and connectivity among phases and existing crack patterns that often take place in composite materials, being these features crucial in order to obtain more reliable safety factors and fatigue life predictions. The methodology has been successfully applied for the characterization of a complex case study, where an uncertainty assessment has been carried out by means of multiple equally likely realizations.Llopis-Albert, C.; Rubio Montoya, FJ.; Valero Chuliá, FJ.; Liao, H.; Zeng, S. (2019). 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