Search Results - acm: c.: computer system organisation/c.1: processes architectural/c.1.4: parallel architectural

Architectural design for resilience.

Authors: Liu, Dong Deters, Ralph Zhang, W.J.

Source: Enterprise Information Systems; May2010, Vol. 4 Issue 2, p137-152, 16p, 1 Color Photograph, 1 Black and White Photograph, 2 Diagrams

Subject Terms: ARCHITECTURAL design, SOFTWARE architecture, RELIABILITY in engineering, FAULT tolerance (Engineering), SERVICE-oriented architecture (Computer science)

Development, Analysis, and Verification of a Parallel Hybrid Dataflow Computer Architectural Framework and Associated Load-Balancing Strategies and Algorithms via Parallel Simulation.

Authors: Heath, J. Robert Sivanesa, Balasubramanian

Source: Simulation; Jul1997, Vol. 69 Issue 1, p7-25, 19p

Towards Morphogenesis in Architecture.

Authors: Roudavski, Stanislav

Source: International Journal of Architectural Computing; Sep2009, Vol. 7 Issue 3, p346-374, 29p, 2 Color Photographs, 10 Black and White Photographs

Subject Terms: MASS customization, AUTOMATION, COMPUTER-aided design, ARCHITECTURAL design, KNOWLEDGE transfer

Computer utterances: Sequence and event in digital architecture.

Authors: Miranda, Pablo

Source: International Journal of Architectural Computing; Dec2017, Vol. 15 Issue 4, p268-284, 17p

Subject Terms: ARCHITECTURE & technology, HYPERSURFACE architecture, COMPUTERS in architecture, COMPUTER-aided design, ARCHITECTURAL design

A Methodology for Architectural Design of Concurrent and Distributed Software Systems.

Authors: Reza, Hassan

Source: Journal of Supercomputing; Sep2006, Vol. 37 Issue 3, p227-248, 22p, 7 Diagrams

Subject Terms: ELECTRONIC systems, SYSTEMS software, COMPUTER systems, PARALLEL computers, COMPUTER hardware description languages, COMPUTER architecture, SYSTEMS development, COMPUTER science, COMPUTERS

THE DiNG - A PARALLEL MULTIATTRIBUTE FILE SYSTEM FOR DEDUCTIVE DATABASE MACHINES.

Authors: Mueck, T. A.

Source: Database Systems For Advanced Applications '93 - Proceedings of the 3rd International Symposium on Database Systems For Advanced Applications; 1993, p115-122, 8p

Subject Terms: DEDUCTIVE databases, DATABASE management, DATA structures, DATALOG (Computer program language), PARALLEL algorithms

Selective Jamming: Digital Architectural Design in Foundation Courses.

Authors: Roudavski, Stanislav

Source: International Journal of Architectural Computing; Dec2011, Vol. 9 Issue 4, p437-462, 26p

Subject Terms: ARCHITECTURAL design, COMPUTER-aided design of buildings, VIRTUAL reality, ARCHITECTURAL education, CREATIVE ability

Geographic Terms: AUSTRALIA

Company/Entity: UNIVERSITY of Melbourne

Diseño Generativo Realimentado (DGR) como soporte en los procesos de creación de productos ; Feedback Generative Design (FGD) as Support in Product Creation Processes

Authors: Restrepo Mendoza, Jhoan Sebastian Cordoba Nieto, Ernesto Grupo de Investigación: Grupo de trabajo en nuevas tecnologías de diseño y manufactura-automatización DIMA-UN

Contributors: Restrepo Mendoza, Jhoan Sebastian Cordoba Nieto, Ernesto Grupo de Investigación: Grupo de trabajo en nuevas tecnologías de diseño y manufactura-automatización DIMA-UN

Subject Terms: 670 - Manufactura, 620 - Ingeniería y operaciones afines, 680 - Manufactura para usos específicos, 600 - Tecnología (Ciencias aplicadas), Diseño industrial, Automatización, Productos nuevos, Diseños de productos, Desarrollo de nuevos productos, Design, industrial, Automation, New products, New product development, Diseño generativo realimentado, Diseño generativo, Optimización multiobjetivo, Diseño paramétrico, Grafos direccionales, Frentes de Pareto, Programación paralela, Feedback-based generative design, Feedback generative design, Generative design, Multi-objective optimization, Parametric design, Directed graphs, Pareto fronts, parallel programming

File Description: xxiii, 206 páginas; application/pdf

Relation: [1] J. S. Restrepo Mendoza and E. Cordoba Nieto, “DISEÑO PARAMÉTRICO PARA CLASIFICACIÓN DE FAMILIAS DE PRODUCTOS EN MANUFACTURA DISCRETA EN EL LABFABEXUN,” in CONGRESO INTERNACIONAL DE INGENIERÍA MECÁNICA, MECATRÓNICA Y AUTOMATIZACIÓN - Memorias 2021, pp. 21–21, 2021.; Martin Hankel, “RAMI4.0 – Reference Architecture Model Industry 4.0.,” 11 2016.; TheOPCFoundation, “RAMI4.0 by Martin Hankel (Bosch-Rexroth) at OPC Day Europe 2016,” 2 2017.; Gonz´alez, “Measurement of Areas on a Sphere Using Fibonacci and Latitude-Longitude Lattices,” Mathematical Geosciences, vol. 42, pp. 49–64, 1 2010.; Departamento Nacional de Planeaci´on (DNP), Superintendencia de Industria y Comercio (SIC), Direcci´on Nacional de Derecho de Autor (DNDA), Instituto Colombiano Agropecuario (ICA), Organizaci´on Mundial de la Propiedad Intelectual (OMPI), and Misi´on permanente de Colombia ante las naciones Unidas, “Reporte sobre la informaci ´on en materia de Propiedad Intelectual en Colombia,” tech. rep., 2017.; J. Mountstephens and J. Teo, “Progress and challenges in generative product design: A review of systems,” 12 2020.; Z. Jiang, H. Wen, F. Han, Y. Tang, and Y. Xiong, “Data-driven generative design for mass customization: A case study,” Advanced Engineering Informatics, vol. 54, 10 2022.; P. Wolniak, B. Sauthoff, D. Kloock-Schreiber, and R. Lachmayer, “AUTOMATED PRODUCT FUNCTIONALITY and DESIGN OPTIMIZATION INSTANCING A PRODUCT-SERVICE SYSTEM,” in Proceedings of the Design Society: DESIGN Conference, vol. 1, pp. 1405–1414, Cambridge University Press, 2020.; M. A. S. Al-Shamsi, “Review of Korean Imitation and Innovation in the Last 60 Years,” 3 2022.; B. Bartikowski, F. Fastoso, and H. Gierl, “Luxury cars Made-in-China: Consequences for brand positioning,” Journal of Business Research, vol. 102, pp. 288–297, 9 2019; K. D. Thoben, S. A. Wiesner, and T. Wuest, “Industrie 4.0 and smart manufacturing-a review of research issues and application examples,” 2017.; D. G. Ullman, The Mechanical Design Process, vol. 1. 2010.; A. M. Farid and N. P. Suh, Axiomatic Design in Large Systems. 2016.; R. L. Norton, Dise˜no de m´aquinas. Un enfoque integrado. Pearson Educaci´on, cuarta edi ed., 2011.; S. BuHamdan, A. Alwisy, and A. Bouferguene, “Generative systems in the architecture, engineering and construction industry: A systematic review and analysis,” International Journal of Architectural Computing, 2020.; D. Nagaraj and D. Werth, “Towards a Generalized System for Generative Engineering,” in ACM International Conference Proceeding Series, Association for Computing Machinery, 1 2020.; S. Fox, “A preliminary methodology for generative production systems,” Journal of Manufacturing Technology Management, vol. 22, no. 3, pp. 348–364, 2011.; A. N. Pilagatti, G. Vecchi, E. Atzeni, L. Iuliano, and A. Salmi, “Generative Design and new designers’ role in the manufacturing industry,” in Procedia CIRP, vol. 112, pp. 364–369, Elsevier B.V., 2022.; C. Hyunjin, “A Study on Application of Generative Design System in Manufacturing Process,” in IOP Conference Series: Materials Science and Engineering, vol. 727, Institute of Physics Publishing, 1 2020.; J.Wu, M. Li, Z. Chen, W. Chen, X.Wu, and Y. Xi, “Generative Design of the Roller Seat of the Wind Turbine Blade Turnover Machine Based on Cloud Computing,” ICMAE 2020 - 2020 11th International Conference on Mechanical and Aerospace Engineering, pp. 212–217, 2020.; H. Li and R. Lachmayer, “Automated exploration of design solution space applying the generative design approach,” in Proceedings of the International Conference on Engineering Design, ICED, vol. 2019-August, pp. 1085–1094, Cambridge University Press, 2019.; S. Khan and M. J. Awan, “A generative design technique for exploring shape variations,” Advanced Engineering Informatics, vol. 38, no. October, pp. 712–724, 2018.; S. Khan, E. Gunpinar, and B. Sener, “GenYacht: An interactive generative design system for computer-aided yacht hull design,” Ocean Engineering, vol. 191, no. August, p. 106462, 2019.; E. Gunpinar and S. Gunpinar, “A shape sampling technique via particle tracing for CAD models,” Graphical Models, vol. 96, no. January, pp. 11–29, 2018; S. Oh, Y. Jung, S. Kim, I. Lee, and N. Kang, “Deep generative design: Integration of topology optimization and generative models,” Journal of Mechanical Design, Transactions of the ASME, vol. 141, 11 2019; P. Ghannad and Y. C. Lee, “Automated modular housing design using a module configuration algorithm and a coupled generative adversarial network (CoGAN),” Automation in Construction, vol. 139, 7 2022; N. A. Kallioras and N. D. Lagaros, “DzAI: Deep learning based generative design,” Procedia Manufacturing, vol. 44, pp. 591–598, 2020; N. A. Kallioras and N. D. Lagaros, “Mlgen: Generative design framework based on machine learning and topology optimization,” Applied Sciences (Switzerland), vol. 11, 12 2021; J. C. Garc´ıa Carrero, Planeaci´on de trayectorias en vuelo de un manipulador industrial para el Laboratorio F´abrica Experimental UN. PhD thesis, Universidad Nacional de Colombia, Bogot´a D.C, 2017; C. Sarmiento Fautoque, Desarrollo Te´orico- Experimental en la Geometr´ıa de Maquinado M´ulti-ejes aplicando Ingenier´ıa Inversa Mixta. PhD thesis, Universidad Nacional de Colombia, Bogot´a D.C., 2014; V. Granadeiro, L. Pina, J. P. Duarte, J. R. Correia, and V. M. Leal, “A general indirect representation for optimization of generative design systems by genetic algorithms: Application to a shape grammar-based design system,” Automation in Construction, vol. 35, pp. 374–382, 2013; H. Li and R. Lachmayer, “Generative Design Approach for Modeling Creative Designs,” IOP Conference Series: Materials Science and Engineering, vol. 408, no. 1, 2018; S. S. Pibal, K. Khoss, and I. Kovacic, “Framework of an algorithm-aided BIM approach for modular residential building information models,” International Journal of Architectural Computing, vol. 20, pp. 777–800, 12 2022; M. Younus, C. Peiyong, L. Hu, and F. Yuqing, “MES development and significant applications in manufacturing -A review,” in ICETC 2010 - 2010 2nd International Conference on Education Technology and Computer, vol. 5, 2010; T. A. Jauhar, M. Safdar, I. Kim, and S. Han, “Web-based Product Data Visualization and Feedback between PLM and MES,” in Proceedings - Web3D 2020: 25th ACM Conference on 3D Web Technology, Association for Computing Machinery, Inc, 11 2020; G. Bruno, A. Faveto, and E. Traini, “An open source framework for the storage and reuse of industrial knowledge through the integration of plm and mes,” Management and Production Engineering Review, vol. 11, pp. 62–73, 6 2020; E. Traini, G. Bruno, A. Awouda, P. Chiabert, and F. Lombardi, “Integration Between PLM and MES for One-of-a-Kind Production,” in IFIP Advances in Information and Communication Technology, vol. 565 IFIP, pp. 356–365, Springer, 2019; M. I. Mahmoud, H. H. Ammar, M. M. Hamdy, and M. H. Eissa, “Production operation management using Manufacturing Execution Systems (MES),” in 2015 11th International Computer Engineering Conference: Today Information Society What’s Next?, ICENCO 2015, pp. 111–116, Institute of Electrical and Electronics Engineers Inc., 2 2016; W. Qifeng and W. Zhangjian, “Web services-based system integration approach for manufacturing execution system,” in Proceedings - 2011 International Conference on Internet Computing and Information Services, ICICIS 2011, pp. 469–472, 2011; S.-H. Jing, Q.-J. Meng, and W.-Q. Cao, “Cement Enterprise MES Key Technology Research and Application,” in 2007 International Conference on Machine Learning and Cybernetics, pp. 277–282, IEEE, 8 2007; W. Qu, W. Cao, and Y. C. Su, “Design and implementation of smart manufacturing execution system in solar industry,” Journal of Ambient Intelligence and Humanized Computing, 2020; Y. Yue-Xina and R. Gong-Chang, “Design of Real Time Data Acquisition System Framework for Production Workshop Based on OPC Technology,” in MATEC Web of Conferences, vol. 128, EDP Sciences, 10 2017; X. Zeng, “Design and implementation of production management system in aviation machining workshop based on MES,” in Proceedings - International Conference on Control Science and Electric Power Systems, CSEPS 2021, pp. 385–388, Institute of Electrical and Electronics Engineers Inc., 5 2021; S. Mantravadi, C. Møller, C. LI, and R. Schnyder, “Design choices for next-generation IIoT-connected MES/MOM: An empirical study on smart factories,” Robotics and Computer-Integrated Manufacturing, vol. 73, 2 2022; J. Barata, P. R. da Cunha, A. S. Gonnagar, and M. Mendes, “Product traceability in ceramic industry 4.0: A design approach and cloud-based MES prototype,” in Lecture Notes in Information Systems and Organisation, vol. 26, pp. 187–204, Springer Heidelberg, 2018; M. Ko, C. Lee, and Y. Cho, “Design and Implementation of Cloud-Based Collaborative Manufacturing Execution System in the Korean Fashion Industry,” Applied Sciences (Switzerland), vol. 12, 9 2022; X. Han, M. Li, and X. Zhang, “Design and key technology of MES for spacecraft assembly,” in Proceedings - 2016 6th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2016, pp. 844–847, Institute of Electrical and Electronics Engineers Inc., 12 2016; D. F. Tosse, S. Araujo, and E. C´ordoba, “Plataforma para integraci´on de m´aquinas en laboratorio f´abrica experimental con enfoque de Industria 4.0,” in Innovar para educar (Corporaci´on Cimted© 2020, ed.), vol. 1, pp. 125–146, Medell´ın, Antioquia – Colombia: Corporaci´on Centro Internacional de Marketing Territorial para la Educaci´on y el Desarrollo, primera ed., 2020; R. Y. Zhong, G. Q. Huang, Q. Y. Dai, K. Zhou, T. Qu, and G. J. Hu, “RFID-enabled real-time manufacturing execution system for discrete manufacturing: Software design and implementation,” in 2011 International Conference on Networking, Sensing and Control, ICNSC 2011, pp. 311–316, 2011; Y. Wang, M. Wang, J. Wang, and Y. Zhou, “Design and implementation of device integration framework based on agent technology in MES,” in Procedia CIRP, vol. 83, pp. 485–489, Elsevier B.V., 2019; G. D’Antonio, F. Segonds, J. S. Bedolla, P. Chiabert, and N. Anwer, “A proposal of manufacturing execution system integration in design for additive manufacturing,” in IFIP Advances in Information and Communication Technology, vol. 467, pp. 761–770, Springer New York LLC, 2016; M. Naedele, H. M. Chen, R. Kazman, Y. Cai, L. Xiao, and C. V. Silva, “Manufacturing execution systems: A vision for managing software development,” Journal of Systems and Software, vol. 101, pp. 59–68, 3 2015; T. Masood and R. H. Weston, “Modelling framework to support decision-making in manufacturing enterprises,” Advances in Decision Sciences, vol. 2013, 2013; H. Habib, R. Menhas, and O. McDermott, “Managing Engineering Change within the Paradigm of Product Lifecycle Management,” Processes, vol. 10, 9 2022; M. Hayat and H. Winkler, “Exploring the Basic Features and Challenges of Traditional Product Lifecycle Management Systems,” in IEEE International Conference on Industrial Engineering and Engineering Management, vol. 2022-December, pp. 762–766, IEEE Computer Society, 2022; S. R¨adler and E. Rigger, “A Survey on the Challenges Hindering the Application of Data Science, Digital Twins and Design Automation in Engineering Practice,” in Proceedings of the Design Society, vol. 2, pp. 1699–1708, Cambridge University Press, 5 2022; S. Nzetchou, A. Durupt, S. Remy, and B. Eynard, “Semantic enrichment approach for low-level CAD models managed in PLM context: Literature review and research prospect,” Computers in Industry, vol. 135, 2 2022; M. Lennartsson, S. Andr´e, and F. Elgh, “PLM support for design platforms in industrialized house-building,” Construction Innovation, 2 2021; V. Kopei, O. Onysko, C. Barz, P. Daˇsi´c, and V. Panchuk, “Designing a Multi-Agent PLM System for Threaded Connections Using the Principle of Isomorphism of Regularities of Complex Systems,” Machines, vol. 11, 2 2023; Y. Liao, F. Deschamps, E. d. F. R. Loures, and L. F. P. Ramos, “Past, present and future of Industry 4.0 - a systematic literature review and research agenda proposal,” International Journal of Production Research, vol. 55, no. 12, pp. 3609–3629, 2017; J. W. Veile, D. Kiel, J. M. M¨uller, and K. I. Voigt, “Lessons learned from Industry 4.0 implementation in the German manufacturing industry,” Journal of Manufacturing Technology Management, 2019; “Status Report Reference Architecture Model Industrie 4.0 (RAMI4.0),” tech. rep., 2015; A. F. Cifuentes G´omez, Implementaci´on de sistemas de gesti´on de informaci´on del ciclo de vida de producto basado en el desarrollo de un molde de inyecci´on. PhD thesis, Universidad Nacional de Colombia, Bogot´a, Colombia, 2021; P. Andr´es and C. Parra, “Modelo e-Manufacturing bajo la arquitectura Cloud Manufacturing para el Laboratorio F´abrica Experimental UN,” tech. rep., 2015; M. K. Mohanty, P. Gahan, and S. Choudhury, “Why most of the supplier development programs fail in discrete manufacturing – findings from selected Indian discrete manufacturing industries,” 2014; T. Yang, X. Yi, J. Wu, Y. Yuan, D. Wu, Z. Meng, Y. Hong, H. Wang, Z. Lin, and K. H. Johansson, “A survey of distributed optimization,” Annual Reviews in Control, vol. 47, pp. 278–305, 2019; A. K. Sethi and S. P. Sethi, “Flexibility in manufacturing: A survey,” International Journal of Flexible Manufacturing Systems, vol. 2, no. 4, pp. 289–328, 1990.; S. K. Saren and V. Tiberiu, “Review of Flexible Manufacturing System Based on Modeling and Simulation,” ANNALS OF THE ORADEA UNIVERSITY. Fascicle of Management and Technological Engineering., vol. Volume XXV, no. 1, 2016.; G. Kim, Y. Kwon, E. S. Suh, and J. Ahn, “Analysis of Architectural Complexity for Product Family and Platform,” Journal of Mechanical Design, Transactions of the ASME, vol. 138, no. 7, pp. 1–11, 2016; O. Asikoglu and T. W. Simpson, “A new method for evaluating design dependencies in product architectures,” 12th AIAA Aviation Technology, Integration and Operations (ATIO) Conference and 14th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, no. September, pp. 1–11, 2012; M. Lafou, L. Mathieu, S. Pois, and M. Alochet, “Manufacturing System Flexibility: Product Flexibility Assessment,” Procedia CIRP, vol. 41, pp. 99–104, 2016.; F. M. Kasie, G. Bright, and A. Walker, “Decision support systems in manufacturing: a survey and future trends,” Journal of Modelling in Management, vol. 12, no. 3, pp. 432– 454, 2017.; J. Igba, K. Alemzadeh, P. M. Gibbons, and K. Henningsen, “A framework for optimising product performance through feedback and reuse of in-service experience,” Robotics and Computer-Integrated Manufacturing, vol. 36, pp. 2–12, 2015; M. von Stietencron, K. A. Hribernik, C. C. Røstad, B. Henriksen, and K. D. Thoben, “Applying closed-loop product lifecycle management to enable fact based design of boats,” in IFIP Advances in Information and Communication Technology, vol. 517, pp. 522–531, Springer New York LLC, 2017; C. a. Coello Coello and G. B. Lamont, Applications Of Multi-Objective Evolutionary Algorithms. 2004; H. Ishibuchi, N. Tsukamoto, and Y. Nojima, “Evolutionary many-objective optimization: A short review,” in 2008 IEEE Congress on Evolutionary Computation, CEC 2008, 2008.; G. Chiandussi, M. Codegone, S. Ferrero, and F. E. Varesio, “Comparison of multiobjective optimization methodologies for engineering applications,” Computers and Mathematics with Applications, vol. 63, no. 5, pp. 912–942, 2012.; G. Ortega, E. Filatovas, E. M. Garz´on, and L. G. Casado, “Non-dominated sorting procedure for Pareto dominance ranking on multicore CPU and/or GPU,” Journal of Global Optimization, vol. 69, pp. 607–627, 11 2017; L. B. De Oliveira, C. G. Marcelino, A. Milanes, P. E. Almeida, and L. M. Carvalho, “A successful parallel implementation of NSGA-II on GPU for the energy dispatch problem on hydroelectric power plants,” in 2016 IEEE Congress on Evolutionary Computation, CEC 2016, pp. 4305–4312, Institute of Electrical and Electronics Engineers Inc., 11 2016.; K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, “A fast and elitist multiobjective genetic algorithm: NSGA-II,” IEEE Transactions on Evolutionary Computation, vol. 6, no. 2, pp. 182–197, 2002.; E. Zitzler, M. Laumanns, and L. Thiele, “SPEA2: Improving the Strength Pareto Evolutionary Algorithm,” Evolutionary Methods for Design Optimization and Control with Applications to Industrial Problems, pp. 95–100, 2001; P. K. Tripathi, S. Bandyopadhyay, and S. K. Pal, “Multi-Objective Particle Swarm Optimization with time variant inertia and acceleration coefficients,” Information Sciences, vol. 177, pp. 5033–5049, 11 2007.; X. Li, “A Non-dominated Sorting Particle Swarm Optimizer for Multiobjective Optimization,” Genetic and Evolutionary Computation — GECCO 2003, vol. 2723, pp. 37–48, 6 2003; R. Sedgewick and K. Wayne, “Algorithms,” tech. rep; J. J. Craig, P. Prentice, and P. P. Hall, “Introduction to Robotics Mechanics and Control Third Edition,” tech. rep., 2005.; I. Viana, J.-J. Orteu, N. Cornille, and F. Bugarin, “Inspection of aeronautical mechanical parts with a pan-tilt-zoom camera: an approach guided by the computer-aided design model,” Journal of Electronic Imaging, vol. 24, no. 6, p. 061118, 2015; H. Huang, J. Liu, S. Liu, T. Wu, and P. Jin, “A method for classifying tube structures based on shape descriptors and a random forest classifier,” Measurement: Journal of the International Measurement Confederation, vol. 158, p. 107705, 2020; F. Hui, P. Payeur, and A. M. Cretu, “Visual tracking of deformation and classification of non-rigid objects with robot hand probing,” Robotics, vol. 6, no. 1, 2017.; J. K. Oh, S. Lee, and C. H. Lee, “Stereo vision based automation for a bin-picking solution,” International Journal of Control, Automation and Systems, vol. 10, no. 2, pp. 362–373, 2012; E. Gunpinar and S. Khan, A multi-criteria based selection method using non-dominated sorting for genetic algorithm based design. No. 65, Springer US, 2019; https://repositorio.unal.edu.co/handle/unal/85019; Universidad Nacional de Colombia; Repositorio Institucional Universidad Nacional de Colombia; https://repositorio.unal.edu.co/

Availability: https://repositorio.unal.edu.co/handle/unal/85019
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Extending reference architecture of big data systems towards machine learning in edge computing environments.

Authors: Pääkkönen, P. Pakkala, D.

Source: Journal of Big Data; 4/6/2020, Vol. 7 Issue 1, p1-29, 29p

Subject Terms: BIG data, MACHINE learning, SOFTWARE engineering, ARCHITECTURAL design, COMPUTER vision, ARCHITECTURAL details

Paneling Architectural Freeform Surfaces.

Authors: Eigensatz, Michael Kilian, Martin Schiftner, Alexander et al.

Source: ACM Transactions on Graphics; Jul2010, Vol. 29 Issue 4, p45:1-45:10, 10p, 8 Color Photographs, 3 Diagrams, 2 Graphs

Subject Terms: ARCHITECTURAL design, COMPUTER-aided design, COMPUTER-aided engineering, ENGINEERING design, COMPUTER simulation

Traceability of Architectural Design Decisions and Software Artifacts: A Systematic Mapping Study.

Authors: Hyun, Santiago Hurtado, Julio Ariel

Source: Foundations of Computing & Decision Sciences; Dec2023, Vol. 48 Issue 4, p401-423, 23p

Subject Terms: ARCHITECTURAL design, DESIGN software, COST overruns, SOFTWARE architecture, DATA mining, COMPUTER software development

Multiprocessor platform-based design for multimedia.

Authors: Ammari, A. C. Jemai, A.

Source: IET Computers & Digital Techniques (Institution of Engineering & Technology); Jan2009, Vol. 3 Issue 1, p52-61, 10p, 5 Diagrams, 2 Charts, 2 Graphs

Subject Terms: EMBEDDED computer systems, ARCHITECTURAL designs, COMPUTER architecture, SYSTEMS design, INTEGRATED circuits, APPLICATION-specific integrated circuits

Parallel programming on a high-performance application-runtime.

Authors: Goscinski, Wojtek James Abramson, David

Source: Concurrency & Computation: Practice & Experience; Dec2008, Vol. 20 Issue 18, p2141-2177, 37p, 9 Diagrams, 11 Graphs

Subject Terms: HIGH performance computing, GRID computing, COMPUTER software development, PARALLEL programming, ARCHITECTURAL design, PROGRAMMING languages, VIRTUAL machine systems

Reliability evaluation of software architectural styles based on correlated component failure.

Authors: Emadi, S.

Source: Scientia Iranica. Transaction D, Computer Science & Engineering & Electrical Engineering; Jan/Feb2022, Vol. 29 Issue 1, p135-149, 15p

Subject Terms: SOFTWARE architecture, COMPUTER software usability, DISCRETE-time systems, MARKOV processes, BINOMIAL distribution

Pinnacles of software engineering: 25 years of formal methods.

Authors: Bjørner, Dines

Source: Annals of Software Engineering; 2000, Vol. 10 Issue 1-4, p11-66, 56p

Subject Terms: SOFTWARE engineering, ELECTRONIC systems, INDUSTRIAL arts, COMPUTER software, ARCHITECTURAL designs, COMPUTER software development, FORMAL methods (Computer science), SYSTEMS design, COMPUTER architecture

Software Architectural Migration: An Automated Planning Approach.

Authors: CHONDAMRONGKUL, NACHA JING SUN WARREN, IAN

Source: ACM Transactions on Software Engineering & Methodology; Jul2021, Vol. 30 Issue 4, p1-35, 35p

Subject Terms: AUTOMATED planning & scheduling, ARCHITECTURAL style, SYSTEM failures, APPLICATION software, ARCHITECTURAL design

Softarch: Tool Support for Integrated Software Architecture Development.

Authors: Grundy, John Hosking, John

Source: International Journal of Software Engineering & Knowledge Engineering; Apr2003, Vol. 13 Issue 2, p125, 27p

Subject Terms: COMPUTER software, OBJECT-oriented methods (Computer science)

Design and Implementation of Face Detection Architecture for Heterogeneous System-on-Chip.

Authors: Panda, Nidhi Gupta, Supratim

Source: Journal of Circuits, Systems & Computers; 2023, Vol. 32 Issue 2, p1-21, 21p

Subject Terms: SYSTEMS on a chip, COMPUTER vision, HUMAN-computer interaction, PARALLEL processing, ARCHITECTURAL design, HUMAN facial recognition software

Phase-Change Memory: An Architectural Perspective.

Authors: ZILBERBERG, OMER WEISS, SHLOMO TOLEDO, SIVAN

Source: ACM Computing Surveys; Jun2013, Vol. 45 Issue 3, p29:1-29:33, 33p, 10 Diagrams, 1 Chart, 1 Graph

Subject Terms: COMPUTER architecture, PHASE change memory, DYNAMIC random access memory, ARCHITECTURAL design, DATA protection, COMPUTER systems

Architectural support for business intelligence: a push-pull mechanism.

Authors: Hua, Jing-Shiuan Huang, Shi-Ming Yen, David C.

Source: Online Information Review; 2012, Vol. 36 Issue 1, p52-71, 20p

Subject Terms: XML (Extensible Markup Language), BUSINESS intelligence, DATABASE management, COMPUTER architecture