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Articoli di riviste sul tema "Computation"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 25 luglio 2025

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1

Brock, Oliver. "Intelligence as Computation." IOP Conference Series: Materials Science and Engineering 1321, no. 1 (2024): 012001. https://doi.org/10.1088/1757-899x/1321/1/012001.

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Abstract This paper proposes a specific conceptualization of intelligence as computation. This conceptualization is intended to provide a unified view for all disciplines of intelligence research. Already, it unifies several conceptualizations currently under investigation, including physical, neural, embodied, morphological, and mechanical intelligences. To achieve this, the proposed conceptualization explains the differences among existing views by different computational paradigms, such as digital, analog, mechanical, or morphological computation. Viewing intelligence as a composition of co

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Olakanmi, Oladayo Olufemi, and Adedamola Dada. "An Efficient Privacy-preserving Approach for Secure Verifiable Outsourced Computing on Untrusted Platforms." International Journal of Cloud Applications and Computing 9, no. 2 (2019): 79–98. http://dx.doi.org/10.4018/ijcac.2019040105.

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In outsourcing computation models, weak devices (clients) increasingly rely on remote servers (workers) for data storage and computations. However, most of these servers are hackable or untrustworthy, which makes their computation questionable. Therefore, there is need for clients to validate the correctness of the results of their outsourced computations and ensure that servers learn nothing about their clients other than the outputs of their computation. In this work, an efficient privacy preservation validation approach is developed which allows clients to store and outsource their computat

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Fresco, Nir. "Long-arm functional individuation of computation." Synthese 199, no. 5-6 (2021): 13993–4016. http://dx.doi.org/10.1007/s11229-021-03407-x.

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AbstractA single physical process may often be described equally well as computing several different mathematical functions—none of which is explanatorily privileged. How, then, should the computational identity of a physical system be determined? Some computational mechanists hold that computation is individuated only by either narrow physical or functional properties. Even if some individuative role is attributed to environmental factors, it is rather limited. The computational semanticist holds that computation is individuated, at least in part, by semantic properties. She claims that the m

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4

Larsen, Brett W., and Shaul Druckmann. "Towards a more general understanding of the algorithmic utility of recurrent connections." PLOS Computational Biology 18, no. 6 (2022): e1010227. http://dx.doi.org/10.1371/journal.pcbi.1010227.

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Lateral and recurrent connections are ubiquitous in biological neural circuits. Yet while the strong computational abilities of feedforward networks have been extensively studied, our understanding of the role and advantages of recurrent computations that might explain their prevalence remains an important open challenge. Foundational studies by Minsky and Roelfsema argued that computations that require propagation of global information for local computation to take place would particularly benefit from the sequential, parallel nature of processing in recurrent networks. Such “tag propagation”

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MACLENNAN, BRUCE J. "EMBODIED COMPUTATION: APPLYING THE PHYSICS OF COMPUTATION TO ARTIFICIAL MORPHOGENESIS." Parallel Processing Letters 22, no. 03 (2012): 1240013. http://dx.doi.org/10.1142/s0129626412400130.

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We discuss the problem of assembling complex physical systems that are structured from the nanoscale up through the macroscale, and argue that embryological morphogenesis provides a good model of how this can be accomplished. Morphogenesis (whether natural or artificial) is an example of embodied computation, which exploits physical processes for computational ends, or performs computations for their physical effects. Examples of embodied computation in natural morphogenesis can be found at many levels, from allosteric proteins, which perform simple embodied computations, up through cells, whi

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6

Aho, A. V. "Computation and Computational Thinking." Computer Journal 55, no. 7 (2012): 832–35. http://dx.doi.org/10.1093/comjnl/bxs074.

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7

Smolensky, Paul. "Symbolic functions from neural computation." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 370, no. 1971 (2012): 3543–69. http://dx.doi.org/10.1098/rsta.2011.0334.

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Is thought computation over ideas? Turing, and many cognitive scientists since, have assumed so, and formulated computational systems in which meaningful concepts are encoded by symbols which are the objects of computation. Cognition has been carved into parts, each a function defined over such symbols. This paper reports on a research program aimed at computing these symbolic functions without computing over the symbols. Symbols are encoded as patterns of numerical activation over multiple abstract neurons, each neuron simultaneously contributing to the encoding of multiple symbols. Computati

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8

Raussendorf, Robert. "Cohomological framework for contextual quantum computations." quantum Information and Computation 19, no. 13&14 (2019): 1141–70. http://dx.doi.org/10.26421/qic19.13-14-4.

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We describe a cohomological framework for measurement-based quantum computation in which symmetry plays a central role. Therein, the essential information about the computation is contained in either of two topological invariants, namely two cohomology groups. One of them applies only to deterministic quantum computations, and the other to general probabilistic ones. Those invariants characterize the computational output, and at the same time witness quantumness in the form of contextuality. In result, they give rise to fundamental algebraic structures underlying quantum computation.

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9

Mussabayev, Rustam. "Optimizing Euclidean Distance Computation." Mathematics 12, no. 23 (2024): 3787. https://doi.org/10.3390/math12233787.

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This paper presents a comparative analysis of seventeen different approaches to optimizing Euclidean distance computations, which is a core mathematical operation that plays a critical role in a wide range of algorithms, particularly in machine learning and data analysis. The Euclidean distance, being a computational bottleneck in large-scale optimization problems, requires efficient computation techniques to improve the performance of various distance-dependent algorithms. To address this, several optimization strategies can be employed to accelerate distance computations. From spatial data s

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10

Burgin, Mark, Eugene Eberbach, and Rao Mikkilineni. "Processing Information in the Clouds." Proceedings 47, no. 1 (2020): 25. http://dx.doi.org/10.3390/proceedings2020047025.

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Cloud computing makes the necessary resources available to the appropriate computation to improve scaling, resiliency, and the efficiency of computations. This makes cloud computing a new paradigm for computation by upgrading its artificial intelligence (AI) to a higher order. To explore cloud computing using theoretical tools, we use cloud automata as a new model for computation. Higher-level AI requires infusing features of the human brain into AI systems such as incremental learning all the time. Consequently, we propose computational models that exhibit incremental learning without stoppin

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Burgin, Mark, Eugene Eberbach, and Rao Mikkilineni. "Processing Information in the Clouds." Proceedings 47, no. 1 (2020): 25. http://dx.doi.org/10.3390/proceedings47010025.

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Cloud computing makes the necessary resources available to the appropriate computation to improve scaling, resiliency, and the efficiency of computations. This makes cloud computing a new paradigm for computation by upgrading its artificial intelligence (AI) to a higher order. To explore cloud computing using theoretical tools, we use cloud automata as a new model for computation. Higher-level AI requires infusing features of the human brain into AI systems such as incremental learning all the time. Consequently, we propose computational models that exhibit incremental learning without stoppin

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12

SADAKANE, Kunihiko, Noriko SUGAWARA, and Takeshi TOKUYAMA. "Quantum Computation in Computational Geometry." Interdisciplinary Information Sciences 8, no. 2 (2002): 129–36. http://dx.doi.org/10.4036/iis.2002.129.

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13

Miller, Douglas A., and Steven W. Zucker. "Cliques, computation, and computational tractability." Pattern Recognition 33, no. 4 (2000): 535–42. http://dx.doi.org/10.1016/s0031-3203(99)00070-9.

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Vyas, Saurabh, Matthew D. Golub, David Sussillo, and Krishna V. Shenoy. "Computation Through Neural Population Dynamics." Annual Review of Neuroscience 43, no. 1 (2020): 249–75. http://dx.doi.org/10.1146/annurev-neuro-092619-094115.

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Significant experimental, computational, and theoretical work has identified rich structure within the coordinated activity of interconnected neural populations. An emerging challenge now is to uncover the nature of the associated computations, how they are implemented, and what role they play in driving behavior. We term this computation through neural population dynamics. If successful, this framework will reveal general motifs of neural population activity and quantitatively describe how neural population dynamics implement computations necessary for driving goal-directed behavior. Here, we

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15

Ghorbani, Mahdi, Mathieu Huot, Shideh Hashemian, and Amir Shaikhha. "Compiling Structured Tensor Algebra." Proceedings of the ACM on Programming Languages 7, OOPSLA2 (2023): 204–33. http://dx.doi.org/10.1145/3622804.

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Tensor algebra is essential for data-intensive workloads in various computational domains. Computational scientists face a trade-off between the specialization degree provided by dense tensor algebra and the algorithmic efficiency that leverages the structure provided by sparse tensors. This paper presents StructTensor, a framework that symbolically computes structure at compilation time. This is enabled by Structured Tensor Unified Representation (STUR), an intermediate language that can capture tensor computations as well as their sparsity and redundancy structures. Through a mathematical vi

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Miłkowski, Marcin. "Morphological Computation: Nothing but Physical Computation." Entropy 20, no. 12 (2018): 942. http://dx.doi.org/10.3390/e20120942.

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The purpose of this paper is to argue against the claim that morphological computation is substantially different from other kinds of physical computation. I show that some (but not all) purported cases of morphological computation do not count as specifically computational, and that those that do are solely physical computational systems. These latter cases are not, however, specific enough: all computational systems, not only morphological ones, may (and sometimes should) be studied in various ways, including their energy efficiency, cost, reliability, and durability. Second, I critically an

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17

Kozlov, AP. "Biological Computation and Compatibility Search in the Possibility Space as the Mechanism of Complexity Increase During Progressive Evolution." Evolutionary Bioinformatics 18 (January 2022): 117693432211106. http://dx.doi.org/10.1177/11769343221110654.

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The idea of computational processes, which take place in nature, for example, DNA computation, is discussed in the literature. DNA computation that is going on in the immunoglobulin locus of vertebrates shows how the computations in the biological possibility space could operate during evolution. We suggest that the origin of evolutionarily novel genes and genome evolution constitute the original intrinsic computation of the information about new structures in the space of unrealized biological possibilities. Due to DNA computation, the information about future structures is generated and stor

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18

Hemmo, Meir, and Orly Shenker. "The Multiple-Computations Theorem and the Physics of Singling Out a Computation." Monist 105, no. 2 (2022): 175–93. http://dx.doi.org/10.1093/monist/onab030.

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Abstract The problem of multiple-computations discovered by Hilary Putnam presents a deep difficulty for functionalism (of all sorts, computational and causal). We describe in outline why Putnam’s result, and likewise the more restricted result we call the Multiple-Computations Theorem, are in fact theorems of statistical mechanics. We show why the mere interaction of a computing system with its environment cannot single out a computation as the preferred one amongst the many computations implemented by the system. We explain why nonreductive approaches to solving the multiple-computations pro

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19

Huo, Chao, Peng Lv, and Anbang Sun. "Computational study on the aerodynamics of a long-shrouded contra-rotating rotor in hover." International Journal of Micro Air Vehicles 11 (January 2019): 175682931983368. http://dx.doi.org/10.1177/1756829319833686.

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This paper aims to investigate the aerodynamics including the global performance and flow characteristics of a long-shrouded contra-rotating rotor by developing a full 3D RANS computation. Through validations by current experiments on the same shrouded contra-rotating rotor, the computation using sliding mesh method and the computational zone with an extended nozzle downstream flow field effectively works; the time-averaged solution of the unsteady computation reveals that more uniform flow presents after the downstream rotor, which implies that the rear rotor rotating at opposite direction gr

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Kim, Boram, Kwang Seok Yoon, and Hyung-Jun Kim. "GPU-Accelerated Laplace Equation Model Development Based on CUDA Fortran." Water 13, no. 23 (2021): 3435. http://dx.doi.org/10.3390/w13233435.

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In this study, a CUDA Fortran-based GPU-accelerated Laplace equation model was developed and applied to several cases. The Laplace equation is one of the equations that can physically analyze the groundwater flows, and is an equation that can provide analytical solutions. Such a numerical model requires a large amount of data to physically regenerate the flow with high accuracy, and requires computational time. These numerical models require a large amount of data to physically reproduce the flow with high accuracy and require computational time. As a way to shorten the computation time by app

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21

HAMANN, HEIKO, and HEINZ WÖRN. "EMBODIED COMPUTATION." Parallel Processing Letters 17, no. 03 (2007): 287–98. http://dx.doi.org/10.1142/s0129626407003022.

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The traditional computational devices and models, such as the von Neumann architecture or the Turing machine, are strongly influenced by concepts of central control and perfection. The standard models of computation seem to cover the reality of computation only partially and lack, in particular, in the ability to describe more natural forms of computation. In this paper we propose the concept of embodied computation, a straight forward advancement of well known concepts such as amorphous computing, emergent phenomena and embodied cognitive science. Many embodied microscopic computational devic

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22

Hasler, Jennifer, and Eric Black. "Physical Computing: Unifying Real Number Computation to Enable Energy Efficient Computing." Journal of Low Power Electronics and Applications 11, no. 2 (2021): 14. http://dx.doi.org/10.3390/jlpea11020014.

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Physical computing unifies real value computing including analog, neuromorphic, optical, and quantum computing. Many real-valued techniques show improvements in energy efficiency, enable smaller area per computation, and potentially improve algorithm scaling. These physical computing techniques suffer from not having a strong computational theory to guide application development in contrast to digital computation’s deep theoretical grounding in application development. We consider the possibility of a real-valued Turing machine model, the potential computational and algorithmic opportunities o

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23

Sun, Jiameng, Binrui Zhu, Jing Qin, Jiankun Hu, and Jixin Ma. "Confidentiality-Preserving Publicly Verifiable Computation Schemes for Polynomial Evaluation and Matrix-Vector Multiplication." Security and Communication Networks 2018 (June 21, 2018): 1–15. http://dx.doi.org/10.1155/2018/5275132.

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With the development of cloud services, outsourcing computation tasks to a commercial cloud server has drawn attention of various communities, especially in the Big Data era. Public verifiability offers a flexible functionality in real circumstance where the cloud service provider (CSP) may be untrusted or some malicious users may slander the CSP on purpose. However, sometimes the computational result is sensitive and is supposed to remain undisclosed in the public verification phase, while existing works on publicly verifiable computation (PVC) fail to achieve this requirement. In this paper,

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24

Ernst, Udo, David Rotermund, and Klaus Pawelzik. "Efficient Computation Based on Stochastic Spikes." Neural Computation 19, no. 5 (2007): 1313–43. http://dx.doi.org/10.1162/neco.2007.19.5.1313.

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The speed and reliability of mammalian perception indicate that cortical computations can rely on very few action potentials per involved neuron. Together with the stochasticity of single-spike events in cortex, this appears to imply that large populations of redundant neurons are needed for rapid computations with action potentials. Here we demonstrate that very fast and precise computations can be realized also in small networks of stochastically spiking neurons. We present a generative network model for which we derive biologically plausible algorithms that perform spike-by-spike updates of

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Miłkowski, Marcin. "Computational Mechanisms and Models of Computation." Philosophia Scientae, no. 18-3 (October 1, 2014): 215–28. http://dx.doi.org/10.4000/philosophiascientiae.1019.

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Infante Barbosa, Joaquim. "Symbolic computation in applied computational mechanics." Journal of Symbolic Computation 61-62 (February 2014): 1–2. http://dx.doi.org/10.1016/j.jsc.2013.10.004.

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Brown, B. D., and H. C. Card. "Stochastic neural computation. I. Computational elements." IEEE Transactions on Computers 50, no. 9 (2001): 891–905. http://dx.doi.org/10.1109/12.954505.

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Burgin, Mark, and Rao Mikkililineni. "Seven Layers of Computation: Methodological Analysis and Mathematical Modeling." Filozofia i Nauka Zeszyt specjalny, no. 10 (2022): 11–32. http://dx.doi.org/10.37240/fin.2022.10.zs.1.

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We live in an information society where the usage, creation, distribution, manipulation, and integration of information is a significant activity. Computations allow us to process information from various sources in various forms and use the derived knowledge in improving efficiency and resilience in our interactions with each other and with our environment. The general theory of information tells us that information to knowledge is as energy is to matter. Energy has the potential to create or modify material structures and information has the potential to create or modify knowledge structures

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Magnani, Lorenzo. "Eccentric Computational Embodiments: Cognitive Domestication of External Entities." Proceedings 47, no. 1 (2020): 36. http://dx.doi.org/10.3390/proceedings2020047036.

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Eco-cognitive computationalism sees computation in context, adopting the intellectual visions advanced by the cognitive science perspectives on embodied, situated, and distributed cognition. It is in this framework that we can fruitfully study the relevance in recent computer science devoted to the simplification of cognitive and motor tasks generated in organic entities by the morphological aspects. Ignorant bodies can be cognitively “domesticated” to become useful “mimetic bodies'', which originate eccentric new computational embodiments capable of rendering an involved computation simpler a

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Magnani, Lorenzo. "Eccentric Computational Embodiments: Cognitive Domestication of External Entities." Proceedings 47, no. 1 (2020): 36. http://dx.doi.org/10.3390/proceedings47010036.

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Eco-cognitive computationalism sees computation in context, adopting the intellectual visions advanced by the cognitive science perspectives on embodied, situated, and distributed cognition. It is in this framework that we can fruitfully study the relevance in recent computer science devoted to the simplification of cognitive and motor tasks generated in organic entities by the morphological aspects. Ignorant bodies can be cognitively “domesticated” to become useful “mimetic bodies'', which originate eccentric new computational embodiments capable of rendering an involved computation simpler a

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Bian, Haoyu, Qichen Tan, Siyang Zhong, and Xin Zhang. "Efficient computation of broadband noise propagation using Gaussian beam tracing method." Journal of the Acoustical Society of America 151, no. 5 (2022): 3387–97. http://dx.doi.org/10.1121/10.0011399.

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The Gaussian beam tracing method has advantages in computing long-distance noise propagation in outdoor environments due to its high efficiency. Usually, repeated computations are required if the target sound wave is broadband or contains multiple frequencies because the method was developed in the frequency domain. This paper presents an efficient computation of broadband noise propagation using Gaussian beam tracing. The approach is based on the fact that the ray behaviors and source properties can be decoupled at high frequencies, where the wave equation is asymptotically solved. Consequent

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Driscoll, Laura N., Krishna Shenoy, and David Sussillo. "Flexible multitask computation in recurrent networks utilizes shared dynamical motifs." Nature Neuroscience 27, no. 7 (2024): 1349–63. http://dx.doi.org/10.1038/s41593-024-01668-6.

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AbstractFlexible computation is a hallmark of intelligent behavior. However, little is known about how neural networks contextually reconfigure for different computations. In the present work, we identified an algorithmic neural substrate for modular computation through the study of multitasking artificial recurrent neural networks. Dynamical systems analyses revealed learned computational strategies mirroring the modular subtask structure of the training task set. Dynamical motifs, which are recurring patterns of neural activity that implement specific computations through dynamics, such as a

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Xia, Gongyu, Jiacheng Liu, Qilin Hong, Pingyu Zhu, Ping Xu, and Zhihong Zhu. "An Efficient Frequency Encoding Scheme for Optical Convolution Accelerator." Photonics 12, no. 1 (2024): 26. https://doi.org/10.3390/photonics12010026.

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In today’s era where the demand for computational resources by large models is increasingly high, optical computing offers an alternative physical platform for computation. With its high parallelism and the maturation of integrated photonic technologies, optical computing is expected to further support the computational resources required by large models. For one-dimensional optical convolution accelerators, existing methods can fully utilize the working bandwidth of electro-optic modulators and the frequency resources of light sources. However, most convolution computations currently require

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Cappello, Peter, and Dimitrios Mourloukos. "CX: A Scalable, Robust Network for Parallel Computing." Scientific Programming 10, no. 2 (2002): 159–71. http://dx.doi.org/10.1155/2002/598245.

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CX, a network-based computational exchange, is presented. The system's design integrates variations of ideas from other researchers, such as work stealing, non-blocking tasks, eager scheduling, and space-based coordination. The object-oriented API is simple, compact, and cleanly separates application logic from the logic that supports interprocess communication and fault tolerance. Computations, of course, run to completion in the presence of computational hosts that join and leave the ongoing computation. Such hosts, or producers, use task caching and prefetching to overlap computation with i

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Chien, Hung-Yu. "Authenticated Diffie-Hellman Key Agreement Scheme that Protects Client Anonymity and Achieves Half-Forward Secrecy." Mobile Information Systems 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/354586.

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Authenticated Diffie-Hellman key agreement (D-H key) is the de facto building block for establishing secure session keys in many security systems. Regarding the computations of authenticated D-H key agreement, the operation of modular exponentiation is the most expensive computation, which incurs a heavy loading on those clients where either their computational capacities or their batteries are limited and precious. As client’s privacy is a big concern in several e-commerce applications, it is desirable to extend authenticated D-H key agreement to protect client’s identity privacy. This paper

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Thuruthel, Thomas George, and Fumiya Iida. "Morphological Computation and Control Complexity." IOP Conference Series: Materials Science and Engineering 1261, no. 1 (2022): 012011. http://dx.doi.org/10.1088/1757-899x/1261/1/012011.

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Abstract Morphological computation proposes the idea that in a physical system, certain computational processes can be off-loaded to the body. However, the concept has still eluded serious theoretical quantification attempts, unlike traditional computational theory. This perspective examines the notion of morphological computation from the well established theories of traditional computation and computational complexity, drawing parallels between the two, to understand the differences and similarities. Further, we look at the quantification efforts of morphological computation and attempt to l

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Sarpeshkar, R. "Analog synthetic biology." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 372, no. 2012 (2014): 20130110. http://dx.doi.org/10.1098/rsta.2013.0110.

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We analyse the pros and cons of analog versus digital computation in living cells. Our analysis is based on fundamental laws of noise in gene and protein expression, which set limits on the energy, time, space, molecular count and part-count resources needed to compute at a given level of precision. We conclude that analog computation is significantly more efficient in its use of resources than deterministic digital computation even at relatively high levels of precision in the cell. Based on this analysis, we conclude that synthetic biology must use analog, collective analog, probabilistic an

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Potter, Aneirin. "044 At what resolution does the brain perform computations?" Journal of Neurology, Neurosurgery & Psychiatry 93, no. 9 (2022): e2.239. http://dx.doi.org/10.1136/jnnp-2022-abn2.88.

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Computation is the transformation of inputs into outputs through logical operations such as AND, OR, and NOT. This literature review compares models of computation at different physiological resolutions, whole brain networks, multi-cell circuits, individual synapses and individual molecular interactions and discusses if these models might be useful for bridging between functional neuroimaging with molecular models of disease. While resolution in functional neuroimaging such as EEG, MEG, PET, and fMRI is of groups of neurons pharmacotherapy alters the brain at a molecular level. Bridging this r

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Yoon, Dong-Hee, and Youngsun Han. "Parallel Power Flow Computation Trends and Applications: A Review Focusing on GPU." Energies 13, no. 9 (2020): 2147. http://dx.doi.org/10.3390/en13092147.

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A power flow study aims to analyze a power system by obtaining the voltage and phase angle of buses inside the power system. Power flow computation basically uses a numerical method to solve a nonlinear system, which takes a certain amount of time because it may take many iterations to find the final solution. In addition, as the size and complexity of power systems increase, further computational power is required for power system study. Therefore, there have been many attempts to conduct power flow computation with large amounts of data using parallel computing to reduce the computation time

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Muñoz, Raül, Ramon Casellas, Ricardo Martínez, and Ricard Vilalta. "PCE: What is It, How Does It Work and What are its Limitations?" IEEE/OSA Journal of Lightwave Technology 32, no. 4 (2014): 528–43. https://doi.org/10.5281/zenodo.58585.

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In GMPLS-controlled optical networks, the utilization of source-based path computation has some limitations, especially in large networks with stringent constraints (e.g., optical impairments) or in multilayer and multidomain networks, which leads to suboptimal routing solutions. The path computation eElement (PCE) can mitigate some weaknesses of GMPLS-controlled optical networks. The main idea behind the PCE is to decouple the path computation function from the GMPLS controllers into a dedicated entity with an open and well-defined interface and protocol. A (stateless) PCE is capable of compu

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TRINDER, P. W., H. W. LOIDL, and R. F. POINTON. "Parallel and Distributed Haskells." Journal of Functional Programming 12, no. 4-5 (2002): 469–510. http://dx.doi.org/10.1017/s0956796802004343.

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Parallel and distributed languages specify computations on multiple processors and have a computation language to describe the algorithm, i.e. what to compute, and a coordination language to describe how to organise the computations across the processors. Haskell has been used as the computation language for a wide variety of parallel and distributed languages, and this paper is a comprehensive survey of implemented languages. We outline parallel and distributed language concepts and classify Haskell extensions using them. Similar example programs are used to illustrate and contrast the coordi

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Kashiwa, Tatsuya. "Large-Scale FDTD Computation as Computational Electromagnetics." IEEJ Transactions on Fundamentals and Materials 129, no. 2 (2009): 50–53. http://dx.doi.org/10.1541/ieejfms.129.50.

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Kashiwa, Tatsuya. "Large-Scale FDTD Computation for Computational Electromagnetics." IEEJ Transactions on Fundamentals and Materials 124, no. 12 (2004): 1129–34. http://dx.doi.org/10.1541/ieejfms.124.1129.

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44

Dayan, P., and J. Williams. "Putting the Computation Back into Computational Modeling." Pharmacopsychiatry 39 (February 2006): 50–51. http://dx.doi.org/10.1055/s-2006-931494.

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45

Sathyan, Sabin, Ugur Aydin, and Anouar Belahcen. "Acoustic Noise Computation of Electrical Motors Using the Boundary Element Method." Energies 13, no. 1 (2020): 245. http://dx.doi.org/10.3390/en13010245.

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Abstract (sommario):

This paper presents a numerical method and computational results for acoustic noise of electromagnetic origin generated by an induction motor. The computation of noise incorporates three levels of numerical calculation steps, combining both the finite element method and boundary element method. The role of magnetic forces in the production of acoustic noise is established in the paper by showing the magneto-mechanical and vibro-acoustic pathway of energy. The conversion of electrical energy into acoustic energy in an electrical motor through electromagnetic, mechanical, or acoustic platforms i

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46

Ravani, B., and Q. J. Ge. "Computation of Spatial Displacements From Geometric Features." Journal of Mechanical Design 115, no. 1 (1993): 95–102. http://dx.doi.org/10.1115/1.2919331.

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Abstract (sommario):

This paper develops the theoretical foundation for computations of spatial displacements from the simple geometric features of points, lines, planes, and their combinations. Using an oriented projective three space with a Clifford Algebra, all these three features are handled in a similar fashion. Furthermore, issues related to uniqueness of computations and minimum number of required features are discussed. It is shown that contrary to the common intuition, specification of a minimum of four points (planes) or three lines are necessary for computation of a unique displacement. Only when the s

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Varley, Thomas F. "A Synergistic Perspective on Multivariate Computation and Causality in Complex Systems." Entropy 26, no. 10 (2024): 883. http://dx.doi.org/10.3390/e26100883.

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Abstract (sommario):

What does it mean for a complex system to “compute” or perform “computations”? Intuitively, we can understand complex “computation” as occurring when a system’s state is a function of multiple inputs (potentially including its own past state). Here, we discuss how computational processes in complex systems can be generally studied using the concept of statistical synergy, which is information about an output that can only be learned when the joint state of all inputs is known. Building on prior work, we show that this approach naturally leads to a link between multivariate information theory a

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48

Protsko, I. O., and D. V. Ostrovka. "ANALYSIS OF THE ERROR OF COMPUTATION FAST TRANSFORMS OF FOURIER CLASS BASED ON CYCLIC CONVOLUTIONS." Ukrainian Journal of Information Technology 2, no. 1 (2020): 52–56. http://dx.doi.org/10.23939/ujit2020.02.052.

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Abstract (sommario):

The features of the computational model of discrete transforms of Fourier class based on cyclic convolutions to determine the algorithmic calculation error are analyzed. Based on the approach of efficient computation of discrete transforms of Fourier class of arbitrary size N, using of a hashing array to transform a discrete basis matrix into a set of block-cyclic submatrices, the components of computational costs are considered. These components of computational costs depend on the type of transform, the size and the block-cycle structure of the transformation core. Examples of computational

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Cooke, Ryan A., and Suhaib A. Fahmy. "Exploring hardware accelerator offload for the Internet of Things." it - Information Technology 62, no. 5-6 (2020): 207–14. http://dx.doi.org/10.1515/itit-2020-0017.

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Abstract (sommario):

AbstractThe Internet of Things is manifested through a large number of low-capability connected devices. This means that for many applications, computation must be offloaded to more capable platforms. While this has typically been cloud datacenters accessed over the Internet, this is not feasible for latency sensitive applications. In this paper we investigate the interplay between three factors that contribute to overall application latency when offloading computations in IoT applications. First, different platforms can reduce computation latency by differing amounts. Second, these platforms

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ONDOCKO, STEFAN, JOZEF SVETLIK, TOMAS STEJSKAL, MICHAL SASALA, and LUKAS HRIVNIAK. "COMPARISON SELECTED NUMERICAL METHODS FOR THE CALCULATION INVERSE KINEMATICS OF NON-STANDARD MODULAR ROBOTIC ARM CONSISTING OF UNIQUE ROTATIONAL MODULES." MM Science Journal 2021, no. 2 (2021): 4468–73. http://dx.doi.org/10.17973/mmsj.2021_6_2021042.

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Abstract (sommario):

The paper compares the most commonly used numerical methods of solving a set of nonlinear equations, especially in terms of computational speed. The methods are applied to a set of nonlinear equations that describe the forward kinematics of a non-standard robotic arm. This arm is an open-loop kinematics chain, composed of special rotary modules. A non-standard feature of the modules is the unlimited rotation around their own axis. This robotic arm consists of six such modules and, thus, has six degrees of freedom. Computations of this nonlinear set of equations are also called inverse kinemati

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