Literatura científica selecionada sobre o tema "Configuration en pipeline"
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Artigos de revistas sobre o assunto "Configuration en pipeline"
WANG, CHENG, e HOWARD M. HEYS. "PERFORMANCE CHARACTERIZATION OF PIPELINED S-BOX IMPLEMENTATIONS FOR THE ADVANCED ENCRYPTION STANDARD". Journal of Circuits, Systems and Computers 23, n.º 03 (março de 2014): 1450036. http://dx.doi.org/10.1142/s0218126614500364.
Texto completo da fonteJ.S., Shijo, e Niranjana Behera. "Modelling and analysis of flow of powders through long pipelines". World Journal of Engineering 17, n.º 5 (15 de julho de 2020): 709–18. http://dx.doi.org/10.1108/wje-01-2020-0035.
Texto completo da fonteZhang, Jiayi, Lin Cui, Hualing Zhai e Dong-Sheng Jeng. "Assessment of Wave–Current-Induced Liquefaction under Twin Pipelines Using the Coupling Model". Journal of Marine Science and Engineering 11, n.º 7 (5 de julho de 2023): 1372. http://dx.doi.org/10.3390/jmse11071372.
Texto completo da fonteAllain, Fabrice, Julien Roméjon, Philippe La Rosa, Frédéric Jarlier, Nicolas Servant e Philippe Hupé. "Geniac: Automatic Configuration GENerator and Installer for nextflow pipelines". Open Research Europe 1 (2 de julho de 2021): 76. http://dx.doi.org/10.12688/openreseurope.13861.1.
Texto completo da fonteTan, Yohei, Daiki Oki, Yu Liu, Yukiko Arai, Zachary Nosker, Haruo Kobayashi, Osamu Kobayashi et al. "Self-Calibration Techniques of Pipeline ADCs Using Cyclic Configuration". Key Engineering Materials 596 (dezembro de 2013): 181–86. http://dx.doi.org/10.4028/www.scientific.net/kem.596.181.
Texto completo da fonteAllain, Fabrice, Julien Roméjon, Philippe La Rosa, Frédéric Jarlier, Nicolas Servant e Philippe Hupé. "Geniac: Automatic Configuration GENerator and Installer for nextflow pipelines". Open Research Europe 1 (21 de fevereiro de 2022): 76. http://dx.doi.org/10.12688/openreseurope.13861.2.
Texto completo da fonteMardonov, B., I. Mirzaev, N. A. Nishonov, E. V. An e E. A. Kosimov. "Upheaval buckling of underground pipelines of complex configuration located in liquefied soils". E3S Web of Conferences 401 (2023): 02041. http://dx.doi.org/10.1051/e3sconf/202340102041.
Texto completo da fonteCheng, Xiaofei, Jun Yang, Tiaojian Xu e Qianyuan Xu. "Study on Hydrodynamic Coefficients of a Submarine Piggyback Pipeline under the Action of Waves and Current". Journal of Marine Science and Engineering 9, n.º 10 (14 de outubro de 2021): 1118. http://dx.doi.org/10.3390/jmse9101118.
Texto completo da fonteCheng, Xiaofei, Jun Yang, Tiaojian Xu e Qianyuan Xu. "Study on Hydrodynamic Coefficients of a Submarine Piggyback Pipeline under the Action of Waves and Current". Journal of Marine Science and Engineering 9, n.º 10 (14 de outubro de 2021): 1118. http://dx.doi.org/10.3390/jmse9101118.
Texto completo da fonteHwang, Woongik, e Jong Seh Lee. "Analytical Model for the Structural Behavior of Pipelines During Lowering-In". Applied Sciences 9, n.º 13 (27 de junho de 2019): 2595. http://dx.doi.org/10.3390/app9132595.
Texto completo da fonteTeses / dissertações sobre o assunto "Configuration en pipeline"
Gasti, Wahida. "Etude et realisation d'un processeur rapide de transformations geometriques d'images numeriques". Université Louis Pasteur (Strasbourg) (1971-2008), 1986. http://www.theses.fr/1986STR13131.
Texto completo da fonteOudrhiri, Ali. "Performance of a Neural Network Accelerator Architecture and its Optimization Using a Pipeline-Based Approach". Electronic Thesis or Diss., Sorbonne université, 2023. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2023SORUS658.pdf.
Texto completo da fonteIn recent years, neural networks have gained widespread popularity for their versatility and effectiveness in solving a wide range of complex tasks. Their ability to learn and make predictions from large data-sets has revolutionized various fields. However, as neural networks continue to find applications in an ever-expanding array of domains, their significant computational requirements become a pressing challenge. This computational demand is particularly problematic when deploying neural networks in resource-constrained embedded devices, especially within the context of edge computing for inference tasks. Nowadays, neural network accelerator chips emerge as the optimal choice for supporting neural networks at the edge. These chips offer remarkable efficiency with their compact size, low power consumption, and reduced latency. Moreover, the fact that they are integrated on the same chip environment also enhances security by minimizing external data communication. In the frame of edge computing, diverse requirements have emerged, necessitating trade-offs in various performance aspects. This has led to the development of accelerator architectures that are highly configurable, allowing them to adapt to distinct performance demands. In this context, the focus lies on Gemini, a configurable inference neural network accelerator designed with imposed architecture and implemented using High-Level Synthesis techniques. The considerations for its design and implementation were driven by the need for parallelization configurability and performance optimization. Once this accelerator was designed, demonstrating the power of its configurability became essential, helping users select the most suitable architecture for their neural networks. To achieve this objective, this thesis contributed to the development of a performance prediction strategy operating at a high-level of abstraction, which considers the chosen architecture and neural network configuration. This tool assists clients in making decisions regarding the appropriate architecture for their specific neural network applications. During the research, we noticed that using one accelerator presents several limits and that increasing parallelism had limitations on performances. Consequently, we adopted a new strategy for optimizing neural network acceleration. This time, we took a high-level approach that did not require fine-grained accelerator optimizations. We organized multiple Gemini instances into a pipeline and allocated layers to different accelerators to maximize performance. We proposed solutions for two scenarios: a user scenario where the pipeline structure is predefined with a fixed number of accelerators, accelerator configurations, and RAM sizes. We proposed solutions to map the layers on the different accelerators to optimise the execution performance. We did the same for a designer scenario, where the pipeline structure is not fixed, this time it is allowed to choose the number and configuration of the accelerators to optimize the execution and also hardware performances. This pipeline strategy has proven to be effective for the Gemini accelerator. Although this thesis originated from a specific industrial need, certain solutions developed during the research can be applied or adapted to other neural network accelerators. Notably, the performance prediction strategy and high-level optimization of NN processing through pipelining multiple instances offer valuable insights for broader application
Lussac, Samuel. "L'Azerbaïdjan, les hydrocarbures et les pipelines : réseaux sociotechniques et régionalisation". Thesis, Bordeaux 4, 2011. http://www.theses.fr/2011BOR40060/document.
Texto completo da fonteThis dissertation looks at the socio-political impacts of the pipelines that have beenimplemented in the South Caucasus since 1991. It is based on a theoreticalframework mixing Actor-Network Theory, Norbert Elias’s sociology andmanagement approaches. It assumes that the construction of an Azerbaijanihydrocarbons transportation complex system sheds light into the evolution of theSouth Caucasian configuration. First, this research studies interactions that emergeLUSSAC Samuel | Science Politique | Doctorat | 201114around the implementation of export routes for Azerbaijani oil and gas resources.It highlights the development of new forms of governance, which mostly benefit tothe oil company BP. Second, this dissertation demonstrates that the sociotechnicalnetworks built around these new export routes contribute to the evolution of theSouth Caucasian configuration. These networks overflow the economic sphere tofoster regionalization between Azerbaijan, Georgia and Turkey. Third, thisresearch underlines the benefits the Azerbaijani ‘state-company’ retrieves fromthis hydrocarbons-based regionalization. Baku takes advantage of oil and gasresources to increase its economic and political influence within the SouthCaucasian configuration. Therefore, the Actor-Network Theory helps to shed lightinto the economic and political role of hydrocarbons in the rise of Azerbaijan.From a failed state, this country has now established itself as a regional power
"The Design and Use of a Smartphone Data Collection Tool and Accompanying Configuration Language". Thesis, 2014. http://hdl.handle.net/10388/ETD-2014-12-1851.
Texto completo da fonteLivros sobre o assunto "Configuration en pipeline"
MORTON, Jaxon. Welding for Beginners: Welding Joint Configurations, Plasma Arc and Hybrid Welding, Pipeline and MIG Welding, Choosing a Welding Career, Making Welding Cart, Math Behind Welding. Independently Published, 2022.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Configuration en pipeline"
Chaganti, Ravikanth. "DSC and the Release Pipeline". In Pro PowerShell Desired State Configuration, 435–52. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3483-9_14.
Texto completo da fonteDingare, Pranoday Pramod. "Understanding the Global Tool Configuration Page". In CI/CD Pipeline Using Jenkins Unleashed, 45–54. Berkeley, CA: Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-7508-5_6.
Texto completo da fonteBrazdil, Pavel, Jan N. van Rijn, Carlos Soares e Joaquin Vanschoren. "Automating Workflow/Pipeline Design". In Metalearning, 123–40. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-67024-5_7.
Texto completo da fonteSun, Xudong, Jiali Lin e Bernd Bischl. "ReinBo: Machine Learning Pipeline Conditional Hierarchy Search and Configuration with Bayesian Optimization Embedded Reinforcement Learning". In Machine Learning and Knowledge Discovery in Databases, 68–84. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43823-4_7.
Texto completo da fonteMo, Fan, Jack C. Chaplin, David Sanderson, Hamood Ur Rehman, Fabio Marco Monetti, Antonio Maffei e Svetan Ratchev. "A Framework for Manufacturing System Reconfiguration Based on Artificial Intelligence and Digital Twin". In Lecture Notes in Mechanical Engineering, 361–73. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18326-3_35.
Texto completo da fonteChaudhary, Hafiz Ahmad Awais, Ivan Guevara, Jobish John, Amandeep Singh, Tiziana Margaria e Dirk Pesch. "Low-Code Internet of Things Application Development for Edge Analytics". In Internet of Things. IoT through a Multi-disciplinary Perspective, 293–312. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18872-5_17.
Texto completo da fonteElkelany, Amany, Robert Ross e Susan Mckeever. "WiFi-Based Human Activity Recognition Using Attention-Based BiLSTM". In Communications in Computer and Information Science, 121–33. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-26438-2_10.
Texto completo da fonteHabekost, Jan-Gerrit, Erik Strahl, Philipp Allgeuer, Matthias Kerzel e Stefan Wermter. "CycleIK: Neuro-inspired Inverse Kinematics". In Artificial Neural Networks and Machine Learning – ICANN 2023, 457–70. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-44207-0_38.
Texto completo da fonteSunwoo, Myoungho, Subramaniam Ganesan e Ka C. Cheok. "A Configuration of Parallel Pipelined Processing with DSP-Based Controller for High-Order Linear Systems". In CAD/CAM Robotics and Factories of the Future, 339–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-52320-5_56.
Texto completo da fonteBekmirzaev, Diyorbek, Ibrakhim Mirzaev, Ruslan Kishanov, Nodirakhon Mansurova e Shoista Sabirova. "Study of the Mass Effect of a Complex Node of UnderGround Pipelines of Orthogonal Configuration Based on Real Earthquake Records". In Lecture Notes in Civil Engineering, 371–83. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-85236-8_34.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Configuration en pipeline"
Dyck, Jason, Stuart Guest, Alireza Kohandehghan e Sean Lepine. "Simulating In-Service Welding of Hot-Tap Branches to Quantify the Effect of Geometry on Level of Restraint". In 2018 12th International Pipeline Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/ipc2018-78600.
Texto completo da fonteGu, Yi, Qishi Wu, Mengxia Zhu e Nageswara S. V. Rao. "Efficient pipeline configuration in distributed heterogeneous computing environments". In the twenty-seventh ACM symposium. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1400751.1400825.
Texto completo da fonteMourelle, Marcio M., Marcos Queija de Siqueira, Gabriela Grisolia de Avila e Ana Lucia F. Lima Torres. "Methodology for Analysis of Installation of a Steel Lazy Wave Riser". In 2004 International Pipeline Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/ipc2004-0110.
Texto completo da fontePaulini, Reinaldo Machado, e Luis Fernando Gonc¸alves Pires. "Optimizing Energy in ORBEL II Oil Pipeline". In 2006 International Pipeline Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/ipc2006-10465.
Texto completo da fonteMeyer, Paul A. "Design Considerations for the Use of Ultrasonic Phased Array Probes in Weld Inspection". In 2000 3rd International Pipeline Conference. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/ipc2000-199.
Texto completo da fonteJuergensen, Birgit, Ivan Ewanicke e Thomas Xi. "Modeling Conflicts and Batch Quality Impacts in Pipeline and Crude Oil Storage Terminal". In 2016 11th International Pipeline Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/ipc2016-64531.
Texto completo da fonteWike, Andrew. "The Pros and Cons of Training Simulator Configurations". In 2004 International Pipeline Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/ipc2004-0049.
Texto completo da fonteHesar, M. "Pipeline-Seabed Interaction in Soft Clay". In ASME 2004 23rd International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2004. http://dx.doi.org/10.1115/omae2004-51425.
Texto completo da fonteAyton, Brent, Thomas Dessein, Alex Fraser, Mari Shironishi, Travis Sera e Daniel Shapiro. "Probabilistic Corrosion Assessment for Natural Gas Storage Wells". In 2022 14th International Pipeline Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/ipc2022-86794.
Texto completo da fonteHaas, Michael, Henrik Witte, Gerhard Kopp e Peter Haberl. "Phased Array Shot Scenario and Shot Sequence Optimization for Crack Detection Inline Inspection Tools". In 2022 14th International Pipeline Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/ipc2022-87765.
Texto completo da fonteRelatórios de organizações sobre o assunto "Configuration en pipeline"
Author, Unknown. PR-322-05215-R02 CFD Analysis of Combined Suction Piping and Casing for Pipeline Pump-Type 12X14X19 DVS-E. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), junho de 2014. http://dx.doi.org/10.55274/r0011038.
Texto completo da fonteBourn. PR-015-05217-R01 High BTU Gas Effects on Performance and Emissions in a Two-Stroke Integral Engine. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), março de 2012. http://dx.doi.org/10.55274/r0010763.
Texto completo da fontePaidoussis, Michael. PR-593-18700-R01 Brine String Dynamics IV Deformation-Vibration in Solution Mined Caverns. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), maio de 2021. http://dx.doi.org/10.55274/r0012099.
Texto completo da fontePerkey, David, David Yearwood, Brian McFall, Brian Harris, Christopher Hardy, Timothy Welp, Adrienne Eckstein e Zachary Tyler. Hydraulic sorting of dredged sediment in a pipeline : an evaluation of the sediment distribution pipe. Engineer Research and Development Center (U.S.), fevereiro de 2024. http://dx.doi.org/10.21079/11681/48219.
Texto completo da fonteDawalibi. L51925 Detection of Anomalies in Coated Pipelines Using Long Range Ultrasonics. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), outubro de 2002. http://dx.doi.org/10.55274/r0010644.
Texto completo da fonteBaete, Christophe. PR-405-163602-R01 Evaluation of AC Corrosion Coupons for Monitoring Applications. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), maio de 2019. http://dx.doi.org/10.55274/r0011593.
Texto completo da fonteBowlin, Elizabeth, Puneet Agarwal e Rhett Dotson. PR-201-153718-R02 Integrity Assessment of DTI Pipelines Using High Resolution NDE. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), abril de 2018. http://dx.doi.org/10.55274/r0011480.
Texto completo da fonteNestleroth. L52298 Augmenting MFL Tools With Sensors that Assess Coating Condition. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), março de 2009. http://dx.doi.org/10.55274/r0010396.
Texto completo da fonteBeavers. L51700 Damage Assessment Tool. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), janeiro de 1993. http://dx.doi.org/10.55274/r0010604.
Texto completo da fonteBaete, Christophe. PR-405-163600-R01 Assessing High Voltage DC Interference Risks on Buried Pipelines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), abril de 2019. http://dx.doi.org/10.55274/r0011566.
Texto completo da fonte