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Relevant bibliographies by topics / Multi-machine

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Academic literature on the topic 'Multi-machine'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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Journal articles on the topic "Multi-machine"

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Shirvani, Mojtaba, Mostafa Abdollahi, Ali Akbar Dusti, and Iman Baghbani. "Wind parks fluctuations at multi machine environment." International Journal of Academic Research 6, no. 3 (2014): 202–7. http://dx.doi.org/10.7813/2075-4124.2014/6-3/a.28.

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M, Lokesh, Raj Kumar K, Shoron J, et al. "Assembly of Multi Filament 3D Printing Machine." International Journal of Research Publication and Reviews 6, no. 3 (2025): 6572–82. https://doi.org/10.55248/gengpi.6.0325.1297.

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Manske, Eberhard, Gerd Jäger, Rostyslav Mastylo, and Denis Dontsov. "NANOPOSITIONING AND NANOMEASURING MACHINE FOR MULTI-SENSOR APPLICATIONS." Measuring Equipment and Metrology 81, no. 2 (2020): 17–24. http://dx.doi.org/10.23939/istcmtm2020.02.017.

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Kawaguchi, Yasuhiro, Keiichi Nakamoto, Toru Ishida, and Yoshimi Takeuchi. "C8 Artistic Machining by Means of Multi-tasking Machine(Multi-axis control machining)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2009.5 (2009): 145–48. http://dx.doi.org/10.1299/jsmelem.2009.5.145.

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Li, Dewei, Wei Zhang, Dongkuan Xu, and Yingjie Tian. "Multi-metrics Classification Machine." Procedia Computer Science 91 (2016): 556–65. http://dx.doi.org/10.1016/j.procs.2016.07.142.

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Akhalaya, B. Kh, Yu Kh Shogenov, S. I. Starovoytov, and A. Kh Shogenov. "Multi-operational Combined Machine." Machinery and Equipment for Rural Area, no. 10 (October 28, 2022): 14–17. http://dx.doi.org/10.33267/2072-9642-2022-10-14-17.

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The features of the operation of a multi-operational combined machine (cultivator) with a universal working device that is inserted into the nose of the cultivator, while the upper half of the device serves as a ripper, and the lower half acts as a slot cutter, are considered. To change the heights of the ripper and slot cutter, it is enough to turn them over 180° when they are put in place. The multi-operational combined tillage machine improved in this way can simultaneously perform several important technological operations: loosening, slotting, milling and leveling the surface with compact

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Moriwaki, T. "Multi-functional machine tool." CIRP Annals 57, no. 2 (2008): 736–49. http://dx.doi.org/10.1016/j.cirp.2008.09.004.

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Niteesh, Kumar, Tanwar Akash, and Upadhyay Hemant. "MULTI OPERATIONAL MACHINE TOOL." International Journal For Applied Research in Science and Engineering 3, no. 2 (2021): 22. https://doi.org/10.5281/zenodo.5168635.

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The concept of Multi-Operational Machine tool is mainly concerned for production based industries. Industries are basically meant for production of useful goods and services at low production cost. We are going to develop a conceptual model of a machine which would be capable of performing different operations simultaneously at high efficiency. The machine proposed in this project can perform tasks like drilling, sawing, cutting and grinding at one work station. The reason to design a multi- operational mechanical machine is that there is no machine which can perform various operations (i.e. d

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Tushar, Lakhmani, Asthana Prakhar, Sharma Mragank, and Verma Vivek. "Multi-Purpose Agriculture Machine." International Journal of Engineering and Management Research 8, no. 3 (2018): 12–14. https://doi.org/10.5281/zenodo.3360177.

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The paper aims on the design, development and the fabrication of the vehicle which can dig the soil, sow the seeds, leveler to close the soil and pump to spray water, these whole systems of the vehicle works with the battery and solar power, the vehicle is controlled by toggle switch. In recent years the development of the autonomous vehicles in the agriculture has experienced increased interest. The advantages of these vehicles are hands-free and fast input operations. In the field of agricultural autonomous vehicle, a concept is been developed to investigate if multiple small autonomous mach

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FUJIOKA, Mikihito, Toshiki HIROGAKI, Eiichi AOYAMA, Keiji OGAWA, and Masatoshi IWAMA. "Development of Multi-functional Mini Machine Tool Integrated Heat Treatment Processes(Advanced machine tool)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2005.2 (2005): 479–84. http://dx.doi.org/10.1299/jsmelem.2005.2.479.

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Dissertations / Theses on the topic "Multi-machine"

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Chow, K. W. "Multi-processor architecture for machine vision." Thesis, Cardiff University, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.358531.

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Garnes, Håvard Husevåg. "Access Control in Multi-Thousand-Machine Datacenters." Thesis, Norwegian University of Science and Technology, Department of Telematics, 2008. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9730.

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<p>Large data centers are used for large-scale high-performance tasks that often includes processing and handling sensitive information. It is therefore important to have access control systems that are able to function in large-scale data centers. This thesis looks into existing solutions for the authentication step of access control in large data centers, and analyses how two authentication systems, Kerberos and PKI, will perform when employed on a larger scale, beyond what is normal in a large data center today. The emphasis in the analysis is on possible bottlenecks in the system, comput

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Kew, Min Shen Peter. "Dynamic analysis of multi-machine electromechanical systems." Thesis, University of Aberdeen, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.290341.

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This thesis describes the detailed modelling procedures for d-q axis representation of multi-machine electromechanical systems. It proposes two methods of connecting electrical machine models which have been formulated in various reference frames, to transmission network models. Investigation of these two methods was accomplished, and the effectiveness and merits of each are fully discussed. Conclusions are drawn which form the bases for recommendation of a connection method for developing a generalised multi-machine power system model. In addition two computer programs are written to provide

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Covella, Vito Vincenzo. "Multi-node Fault Classification using Machine Learning." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/22867/.

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An HPC system, a system with much more computational power than general computing systems, is a complex system made up of different sections and many computing nodes. In such systems failures can arise for different reasons: because of the interactions among the components, because of the specific technologies used or because of bugs in the software. In order to reach Exascale performances and guarantee availability and reliability it is important to detect and recover from these anomalies. In this thesis we propose a fault classification method based on machine learning. Other researchers

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Wong, Chi Man. "Extreme learning machine for multi-class classification." Thesis, University of Macau, 2018. http://umaclib3.umac.mo/record=b3948432.

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Emenonye, Don-Roberts Ugochukwu. "Application of Machine Learning to Multi Antenna Transmission and Machine Type Resource Allocation." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/99956.

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Wireless communication systems is a well-researched area in electrical engineering that has continually evolved over the past decades. This constant evolution and development have led to well-formulated theoretical baselines in terms of reliability and efficiency. However, most communication baselines are derived by splitting the baseband communications into a series of modular blocks like modulation, coding, channel estimation, and orthogonal frequency modulation. Subsequently, these blocks are independently optimized. Although this has led to a very efficient and reliable process, a theoreti

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Monti, Johanna. "Multi-word unit processing in machine translation. Developing and using language resources for multi-word unit processing in machine translation." Doctoral thesis, Universita degli studi di Salerno, 2015. http://hdl.handle.net/10556/2042.

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Lagerkvist, Mikael Zayenz. "Machine Assisted Reasoning for Multi-Threaded Java Bytecode." Thesis, KTH, Electronic, Computer and Software Systems, ECS, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-9512.

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<p>In this thesis an operational semantics for a subset of the Java Virtual Machine (JVM) is developed and presented. The subset contains standard operations such as control flow, computation, and memory management. In addition, the subset contains a treatment of parallel threads of execution.</p><p> </p><p>The operational semantics are embedded into a $µ$-calculus based proof assistant, called the VeriCode Proof Tool (VCPT). VCPT has been developed at the Swedish Institute of Computer Science (SICS), and has powerful features for proving inductive assertions.</p><p> </p><p>Some examples of pr

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葉賜權 and Chee-kuen Yip. "Machine recognition of multi-font printed Chinese Characters." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1990. http://hub.hku.hk/bib/B31210120.

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Pickup, Lyndsey C. "Machine learning in multi-frame image super-resolution." Thesis, University of Oxford, 2007. http://ora.ox.ac.uk/objects/uuid:88c6968f-1e62-4d89-bd70-604bf1f41007.

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Multi-frame image super-resolution is a procedure which takes several noisy low-resolution images of the same scene, acquired under different conditions, and processes them together to synthesize one or more high-quality super-resolution images, with higher spatial frequency, and less noise and image blur than any of the original images. The inputs can take the form of medical images, surveillance footage, digital video, satellite terrain imagery, or images from many other sources. This thesis focuses on Bayesian methods for multi-frame super-resolution, which use a prior distribution over the

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Books on the topic "Multi-machine"

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Schwartz, Howard M. Multi-Agent Machine Learning. John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118884614.

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Jin, Yaochu, ed. Multi-Objective Machine Learning. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/3-540-33019-4.

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Jin, Yaochu, ed. Multi-Objective Machine Learning. Springer-Verlag, 2006. http://dx.doi.org/10.1007/11399346.

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1966-, Jin Yaochu, ed. Multi-objective machine learning. Springer, 2006.

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Kovalev, Mikhail, Silvia M. Müller, and Wolfgang J. Paul. A Pipelined Multi-core MIPS Machine. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13906-7.

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Alkhateeb, Abedalrhman, and Luis Rueda, eds. Machine Learning Methods for Multi-Omics Data Integration. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-36502-7.

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Lutsyk, Petro, Jonas Oberhauser, and Wolfgang J. Paul. A Pipelined Multi-Core Machine with Operating System Support. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43243-0.

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Burns, Claudia. Easy baking: Kenmore Choice bread machine with multi-logic. Cookbook Resource USA, 1993.

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Saxena, Dhish Kumar, Sukrit Mittal, Kalyanmoy Deb, and Erik D. Goodman. Machine Learning Assisted Evolutionary Multi- and Many- Objective Optimization. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-2096-9.

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Radzevich, Stephen P. CAD/CAM of Sculptured Surfaces on Multi-Axis NC Machine. Springer International Publishing, 2008. http://dx.doi.org/10.1007/978-3-031-79312-7.

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Book chapters on the topic "Multi-machine"

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Brecher, Christian, and Manfred Weck. "Multi-Machine Systems." In Lecture Notes in Production Engineering. Springer Berlin Heidelberg, 2024. http://dx.doi.org/10.1007/978-3-662-68120-6_9.

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Mao, Weizhen. "Multi-operation multi-machine scheduling." In High-Performance Computing and Networking. Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/bfb0046606.

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Zhu, Weibin, Shijian Ju, and Hui Wang. "Multi-Mode Shield Machine." In Shield Tunneling Technology in Mixed Face Ground Conditions. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4112-2_8.

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Taleizadeh, Ata Allah. "Multi-product Single Machine." In Imperfect Inventory Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-56974-7_5.

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Fieldsend, Jonathan E. "Regression Error Characteristic Optimisation of Non-Linear Models." In Multi-Objective Machine Learning. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/3-540-33019-4_5.

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Furukawa, Tomonari, Chen Jian Ken Lee, and John G. Michopoulos. "Regularization for Parameter Identification Using Multi-Objective Optimization." In Multi-Objective Machine Learning. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/3-540-33019-4_6.

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Zhang, Jiashuai, Yiwei He, and Jingjing Tang. "Multi-view Multi-task Support Vector Machine." In Lecture Notes in Computer Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93701-4_32.

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Persson, Camille, Gauthier Picard, Fano Ramparany, and Olivier Boissier. "A Multi-agent Based Governance of Machine-to-Machine Systems." In Multi-Agent Systems. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34799-3_14.

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Nguyen, Khanh, Trung Le, Vu Nguyen, and Dinh Phung. "Sparse Adaptive Multi-hyperplane Machine." In Advances in Knowledge Discovery and Data Mining. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31753-3_3.

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Phan, Dzung T., Lam Nguyen, Jayant Kalagnanam, and Chandra Reddy. "Multi-polytope Machine for Classification." In Proceedings of the 2024 SIAM International Conference on Data Mining (SDM). Society for Industrial and Applied Mathematics, 2024. http://dx.doi.org/10.1137/1.9781611978032.13.

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Conference papers on the topic "Multi-machine"

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Wang, Yuxia, Jonibek Mansurov, Petar Ivanov, et al. "M4: Multi-generator, Multi-domain, and Multi-lingual Black-Box Machine-Generated Text Detection." In Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, 2024. https://doi.org/10.18653/v1/2024.eacl-long.83.

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Jakeman, John, Michael Eldred, Gianluca Geraci, et al. "Multi-fidelity Machine Learning." In Proposed for presentation at the Machine Learning and Deep Learning Conference held July 19-22, 2021 in Albuququerque, NM. US DOE, 2021. http://dx.doi.org/10.2172/1876608.

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Lekamalage, Chamara Kasun Liyanaarachchi, Kang Song, Guang-Bin Huang, Dongshun Cui, and Ken Liang. "Multi layer multi objective extreme learning machine." In 2017 IEEE International Conference on Image Processing (ICIP). IEEE, 2017. http://dx.doi.org/10.1109/icip.2017.8296491.

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Nirenburg, Sergei, and Robert Frederking. "Toward multi-engine machine translation." In the workshop. Association for Computational Linguistics, 1994. http://dx.doi.org/10.3115/1075812.1075842.

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Qiu, Weimin, Zhuzhong Qian, and Sanglu Lu. "Multi-Objective Virtual Machine Consolidation." In 2017 IEEE 10th International Conference on Cloud Computing (CLOUD). IEEE, 2017. http://dx.doi.org/10.1109/cloud.2017.42.

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Golushko, D. A., A. V. Lysenko, N. K. Yurkov, P. E. Bushmelev, and M. P. Kalaev. "Multi-channel vibration measurement machine." In 2016 International Conference on Actual Problems of Electron Devices Engineering (APEDE). IEEE, 2016. http://dx.doi.org/10.1109/apede.2016.7879015.

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Dang, Tat-Dat, and Ha-Nam Nguyen. "Multi-class Minimax Probability Machine." In 2009 International Conference on Knowledge and Systems Engineering (KSE). IEEE, 2009. http://dx.doi.org/10.1109/kse.2009.46.

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Xuesen Lin. "Multi-behaviors Finite State Machine." In 2009 IEEE Youth Conference on Information, Computing and Telecommunication (YC-ICT). IEEE, 2009. http://dx.doi.org/10.1109/ycict.2009.5382390.

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Wang, Zhaozhi, Kefan Su, Jian Zhang, et al. "Multi-Agent Automated Machine Learning." In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2023. http://dx.doi.org/10.1109/cvpr52729.2023.01151.

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Fomicheva, Marina, Lucia Specia, and Francisco Guzmán. "Multi-Hypothesis Machine Translation Evaluation." In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, 2020. http://dx.doi.org/10.18653/v1/2020.acl-main.113.

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Reports on the topic "Multi-machine"

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Hamann, Hendrik F. A Multi-scale, Multi-Model, Machine-Learning Solar Forecasting Technology. Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1395344.

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Lauer, E. Multi-Pulse DARHT Machine-Plasma Plume Problem. Office of Scientific and Technical Information (OSTI), 2004. http://dx.doi.org/10.2172/15014621.

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Zhang, Tong. Multi-Stage Convex Relaxation Methods for Machine Learning. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada580533.

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Shamma, J. S., E. Feron, L. Gasser, and T. von Thaden. Coordinated Multi-Disciplinary Design of Complex Human Machine Systems. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada567090.

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Gangloff, John, Wenping Zhao, Soumalya Sarkar, et al. Multi-Source Machine Learning and Thermoplastics Enhanced Aerostructure Manufacturing (mTEAM). Office of Scientific and Technical Information (OSTI), 2024. http://dx.doi.org/10.2172/2314986.

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Klarer, P. R. Flocking small smart machines: An experiment in cooperative, multi-machine control. Office of Scientific and Technical Information (OSTI), 1998. http://dx.doi.org/10.2172/573344.

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Lunn, Maureen, and David Fredenburg. Lab’s Z-machine efforts advance stockpile stewardship in multi-org collaboration. Office of Scientific and Technical Information (OSTI), 2022. http://dx.doi.org/10.2172/1864981.

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Hou, Zhangshuan, Huiying Ren, Arun Veeramany, et al. Multi-scale Multi-physics Scientific Machine Learning for Water Cycle Extreme Events Identification, Labelling, Representation, and Characterization. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1769751.

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SWENSON, C. E. FEMA and RAM Analysis for the Multi Canister Overpack (MCO) Handling Machine. Office of Scientific and Technical Information (OSTI), 2000. http://dx.doi.org/10.2172/803966.

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SWENSON, C. E. Multi Canister Overpack (MCO) Handling Machine Independent Review of Seismic Structural Analysis. Office of Scientific and Technical Information (OSTI), 2000. http://dx.doi.org/10.2172/804802.

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