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Download Special Issue Scientific Programming Scientific Programming Techniques and Algorithms for Data-Intensive Engineering Environments Lead Guest Editor: Giner Alor-Hernandez Guest Editors: Jezreel Mejia-Miranda and José María Álvarez-Rodríguez Scientific Programming Techniques and Algorithms for Data-Intensive Engineering Environments Scientific Programming Scientific Programming Techniques and Algorithms for Data-Intensive Engineering Environments Lead Guest Editor: Giner Alor-Hernández Guest Editors: Jezreel Mejia-Miranda and José María Álvarez-Rodríguez Copyright © 2018 Hindawi. All rights reserved. This is a special issue published in “Scientific Programming.” All articles are open access articles distributed under the Creative Com- mons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Editorial Board M. E. Acacio Sanchez, Spain Christoph Kessler, Sweden Danilo Pianini, Italy Marco Aldinucci, Italy Harald Köstler, Germany Fabrizio Riguzzi, Italy Davide Ancona, Italy José E. Labra, Spain Michele Risi, Italy Ferruccio Damiani, Italy Thomas Leich, Germany Damian Rouson, USA Sergio Di Martino, Italy Piotr Luszczek, USA Giuseppe Scanniello, Italy Basilio B. Fraguela, Spain Tomàs Margalef, Spain Ahmet Soylu, Norway Carmine Gravino, Italy Cristian Mateos, Argentina Emiliano Tramontana, Italy Gianluigi Greco, Italy Roberto Natella, Italy Autilia Vitiello, Italy Bormin Huang, USA Francisco Ortin, Spain Jan Weglarz, Poland Chin-Yu Huang, Taiwan Can Özturan, Turkey Jorn W. Janneck, Sweden Antonio J. Peña, Spain Contents Scientific Programming Techniques and Algorithms for Data-Intensive Engineering Environments Giner Alor-Hernández , Jezreel Mejía-Miranda, and José María Álvarez-Rodríguez Editorial (3 pages), Article ID 1351239, Volume 2018 (2018) Survey of Scientific Programming Techniques for the Management of Data-Intensive Engineering Environments Jose María Álvarez-Rodríguez , Giner Alor-Hernández , and Jezreel Mejía-Miranda Review Article (21 pages), Article ID 8467413, Volume 2018 (2018) Analysis of Medical Opinions about the Nonrealization of Autopsies in a Mexican Hospital Using Association Rules and Bayesian Networks Elayne Rubio Delgado, Lisbeth Rodríguez-Mazahua , José Antonio Palet Guzmán, Jair Cervantes, José Luis Sánchez Cervantes, Silvestre Gustavo Peláez-Camarena, and Asdrúbal López-Chau Research Article (21 pages), Article ID 4304017, Volume 2018 (2018) Scalable Parallel Distributed Coprocessor System for Graph Searching Problems with Massive Data Wanrong Huang, Xiaodong Yi, Yichun Sun, Yingwen Liu, Shuai Ye, and Hengzhu Liu Research Article (9 pages), Article ID 1496104, Volume 2017 (2018) Design and Solution of a Surrogate Model for Portfolio Optimization Based on Project Ranking Eduardo Fernandez, Claudia Gómez-Santillán, Laura Cruz-Reyes, Nelson Rangel-Valdez, and Shulamith Bastiani Research Article (10 pages), Article ID 1083062, Volume 2017 (2018) Semantic Annotation of Unstructured Documents Using Concepts Similarity Fernando Pech, Alicia Martinez, Hugo Estrada, and Yasmin Hernandez Research Article (10 pages), Article ID 7831897, Volume 2017 (2018) Applying Softcomputing for Copper Recovery in Leaching Process Claudio Leiva, Víctor Flores, Felipe Salgado, Diego Poblete, and Claudio Acuña Research Article (6 pages), Article ID 6459582, Volume 2017 (2018) A Heterogeneous System Based on Latent Semantic Analysis Using GPU and Multi-CPU Gabriel A. León-Paredes, Liliana I. Barbosa-Santillán, and Juan J. Sánchez-Escobar Research Article (19 pages), Article ID 8131390, Volume 2017 (2018) Sentiment Analysis in Spanish for Improvement of Products and Services: A Deep Learning Approach Mario Andrés Paredes-Valverde, Ricardo Colomo-Palacios, María del Pilar Salas-Zárate, and Rafael Valencia-García Research Article (6 pages), Article ID 1329281, Volume 2017 (2018) Hindawi Scientific Programming Volume 2018, Article ID 1351239, 3 pages https://doi.org/10.1155/2018/1351239 Editorial Scientific Programming Techniques and Algorithms for Data-Intensive Engineering Environments Giner Alor-Hernández ,1 Jezreel Mej-a-Miranda,2 and José Mar-aÁlvarez-Rodr-guez 3 1 Division of Research and Postgraduate Studies, Instituto Tecnologico´ de Orizaba, Orizaba, VER, Mexico 2Research Center in Mathematics (CIMAT, A. C.), Unit Zacatecas, Zacatecas, ZAC, Mexico 3Department of Engineering and Computer Science, Universidad Carlos III de Madrid, Madrid, Spain Correspondence should be addressed to Giner Alor-Hern´andez; [email protected] Received 18 February 2018; Accepted 19 February 2018; Published 5 November 2018 Copyright © 2018 Giner Alor-Hern´andez et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1. Introduction of new multidisciplinary, data-intensive, and sofware-centric environments. Programming paradigms such as functional, In recent years, the development, advancement, and use of symbolic, logic, linear, or reactive programming in conjunc- Information and Communications Technology (ICT) have tion with development platforms are considered a corner- had a major impact on the operation, structure, and strategy stone for the proper development of intelligent and federated of organizations around the world. Today, it is unthinkable to programming platforms to support continuous and collabo- conceive an organization without the use of ICT, because it rative engineering. allows for the reduction of communication costs and oper- More specifcally, the availability of huge amounts of ation while increasing fexibility, interactivity, performance, data that are continuously generated by persons, tools, sen- and productivity. As a result, digital technology fueled by sors, and any other smart connected device requires new ICT and ICT is currently embedded in any task, activity, and architectures to address the challenge of solving complex process that is done in any organization or even our daily problems such as pattern identifcation, process optimization, life activities. Tis new digital age also implies that science, discovery of interactions, knowledge inference, execution of engineering, and business environments need to reshape large simulations, or machine cooperation. Tis situation their strategies and underlying technology to become a key implies the rethinking and application of innovative scientifc player of the Industrial Revolution 4.0. programming techniques for numerical, scientifc, and engi- Engineering methods such as requirements engineering, neering computation on top of well-defned hardware and systems modeling, complex network analysis, or simulation sofware architectures to support the proper development are currently applied to support the development of criti- and operation of complex systems. cal systems and decision-making processes in operational In this context, the evolution and extension of engi- environments. As an example, cyberphysical systems featured neering methods through scientifc programming techniques by mechanical, electrical, and sofware components are a in data-intensive environments are expected to take advan- major challenge for the industry in which new and integrated tage of innovative algorithms implemented using diferent science and engineering techniques are required to develop programming paradigms and execution platforms. Te con- and operate these systems in a collaborative data-intensive junction of scientifc programming techniques and engineer- environment. ing techniques will support and enhance existing develop- Both the development processes and the operational ment and production environments to provide high qual- environments of complex systems need the application of ity, economical, reliable, and efcient data-centric sofware scientifc and engineering methods to fulfll the management products and services. Tis advance in the feld of scientifc 2 Scientifc Programming programming methods will become a key enabler for the next to achieve high performance and customized memory archi- wave of sofware systems and engineering. tecture to deal with irregular memory access pattern. Terefore, the main objective of this special issue was to In an additional contribution, entitled “Analysis of Med- collect and consolidate innovative and high quality research ical Opinions about the Nonrealization of Autopsies in a contributions regarding scientifc programing techniques Mexican Hospital Using Association Rules and Bayesian and algorithms applied to the enhancement and improve- Networks,” E. R. Delgado identifes the factors infuencing ment of engineering methods to develop real and sustainable the reduction of autopsies in a hospital in Veracruz. Te data-intensive science and engineering environments. study is based on the application of data mining techniques such as association rules and Bayesian networks in datasets 2. Papers created from the opinions of physicians. For the exploration and extraction of the knowledge, some algorithms like Tis special issue aims to provide insights into the recent Apriori, FPGrowth, PredictiveApriori, Tertius, J48, Naive advances in the aforementioned topics by soliciting original Bayes, MultilayerPerceptron, and BayesNet were analyzed. scientifc contributions in the form of theoretical founda- To generate mining models and present the new knowledge tions, models, experimental research, surveys, and case stud-
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