Takahiro Nishimura · 2023
Abstract This chapter presents the concept and implementation of fluorescence energy transfer computing, specifically utilizing Förster resonance energy transfer (FRET) between molecular fluorophores and quantum dots. FRET is a non-radiative form of excitation energy transfer that depends on the configuration and optical properties of molecular fluorophores and quantum dots. By designing energy flows through FRET, signal processing can be implemented to perform desired operations. Because the phenomenon occurs at the nanometer scale, miniaturization of information devices can be expected. This chapter reviews the concepts of FRET computing and the implementation of FRET computing devices. Then, a framework of DNA scaffold logic, which systematically handles FRET-based logic operations, is described. Finally, the idea of a FRET network is discussed as a method for enhancing FRET computing performance.
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Qiang Yang, Yu Zhang, Wenyuan Dai et al. · Cambridge University Press eBooks · 2020
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Smita Krishnaswamy, Igor L. Markov, John P. Hayes · Lecture notes in electrical engineering · 2012
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Valentina Casola, Salvatore Della Torca · 2024
Convolutional Neural Networks (CNNs), have demonstrated remarkable performance across a range of domains, including computer vision and healthcare. However, they encounter challenges related to the increasing demands for resources and their susceptibility to adversarial attacks. Despite the significance of these challenges, they are often addressed independently in the scientific literature, which has led to conflicting findings.
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Yusuke Fujii, Takuya Azumi, Nobuhiko Nishio et al. · 2013 International Conference on Parallel and Distributed Systems · 2013
Graphics processing units (GPUs) embrace many-core compute devices where massively parallel compute threads are offloaded from CPUs. This heterogeneous nature of GPU computing raises non-trivial data transfer problems especially against latency-critical real-time systems. However even the basic characteristics of data transfers associated with GPU computing are not well studied in the literature. In this paper, we investigate and characterize currently-achievable data transfer methods of cutting-edge GPU technology. We implement these methods using open-source software to compare their performance and latency for real-world systems. Our experimental results show that the hardware-assisted direct memory access (DMA) and the I/O read-and-write access methods are usually the most effective, while on-chip micro controllers inside the GPU are useful in terms of reducing the data transfer latency for concurrent multiple data streams. We also disclose that CPU priorities can protect the performance of GPU data transfers.
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OECD · OECD eBooks · 2024
This report provides an international benchmarking of Germany’s artificial intelligence (AI) ecosystem and discusses progress in implementing its national AI strategy. The report draws on quantitative and qualitative data and insights from the OECD.AI Policy Observatory and from the OECD Programme on AI in Work, Innovation, Productivity and Skills (AI-WIPS) – an OECD research programme financed by the German Federal Government – and results from a series of interviews with a wide range of stakeholders in Germany. The review discusses Germany’s strengths, weaknesses, opportunities, and challenges in AI, and provides recommendations to steer AI policy in Germany in the coming years. The evidence is presented according to the core focus areas outlined in Germany’s national AI strategy, which include: 1) minds; 2) research; 3) transfer and applications; 4) the world of work; 5) policy and regulatory frameworks; and 6) society. Furthermore, the report discusses AI infrastructure and it includes three sector spotlights on AI in the public sector, AI and environmental sustainability and AI and healthcare.
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Matthew Harrick · 2019
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Nalini Govindarajulu · RePEc: Research Papers in Economics
Purpose - Although end‐user computing (EUC) training has received significant attention among academics and practitioners, the effective transfer of trained EUC skills is a relatively neglected issue. Analysis of factors affecting the EUC transfer process will aid in understanding and improving training transfer. Hence, the purpose of this paper is to underscore key trainee characteristics and facets of the work environment that influence EUC training transfer. Design/methodology/approach - The theoretical framework includes prior computer experience, computer anxiety, computer self‐efficacy, pre‐training motivation and perceived job utility as significant trainee factors influencing the EUC transfer process. In addition, the model includes supervisory support as an important constituent of the EUC transfer process. Findings - The model highlights the mediating roles of computer self‐efficacy and pre‐training motivation in predicting motivation to transfer. In addition, it points out that several factors work simultaneously to influence motivation to transfer EUC training. Practical implications - Supervisory support in the pre‐ and post‐training environment is extremely crucial in determining EUC training success. Specifically, supervisors should be able to communicate to employees the purpose and importance of training, the relevance of computer training to their jobs and the outcomes expected. Originality/value - This paper contributes to the literature by emphasizing the importance of supervisory support and individual characteristics in predicting motivation to transfer.
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Kohut, Roman · Digital Repository (National Repository of Grey Literature) · 2005
In the paper, the solution of the nonstationary heat equations is described. The parallel computing with the adaptive timestep size is used. For the solution of the linear systems the preconditioned CG method is used with the preconditioning given by the additive overlapping Schwarz method.
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Nalini Govindarajulu · RePEc: Research Papers in Economics
Purpose - Although end‐user computing (EUC) training has received significant attention among academics and practitioners, the effective transfer of trained EUC skills is a relatively neglected issue. Analysis of factors affecting the EUC transfer process will aid in understanding and improving training transfer. Hence, the purpose of this paper is to underscore key trainee characteristics and facets of the work environment that influence EUC training transfer. Design/methodology/approach - The theoretical framework includes prior computer experience, computer anxiety, computer self‐efficacy, pre‐training motivation and perceived job utility as significant trainee factors influencing the EUC transfer process. In addition, the model includes supervisory support as an important constituent of the EUC transfer process. Findings - The model highlights the mediating roles of computer self‐efficacy and pre‐training motivation in predicting motivation to transfer. In addition, it points out that several factors work simultaneously to influence motivation to transfer EUC training. Practical implications - Supervisory support in the pre‐ and post‐training environment is extremely crucial in determining EUC training success. Specifically, supervisors should be able to communicate to employees the purpose and importance of training, the relevance of computer training to their jobs and the outcomes expected. Originality/value - This paper contributes to the literature by emphasizing the importance of supervisory support and individual characteristics in predicting motivation to transfer.
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Jakub Truszkowski, Olivier Gascuel, Krister M. Swenson · bioRxiv (Cold Spring Harbor Laboratory) · 2019
Abstract Given trees T and T * on the same taxon set, the transfer index ϕ ( b, T *) is the number of taxa that need to be ignored so that the bipartition induced by branch b in T is equal to some bipartition in T *. Recently, Lemoine et al . [14] used the transfer index to design a novel bootstrap analysis technique that improves on Felsenstein’s bootstrap on large, noisy data sets. In this work, we propose an algorithm that computes the transfer index for all branches b ∈ T in O ( n log 3 n ) time, which improves upon the current O ( n 2 )-time algorithm by Lin, Rajan and Moret [15]. Our implementation is able to process pairs of trees with hundreds of thousands of taxa in minutes and considerably speeds up the method of Lemoine et al . on large data sets. We believe our algorithm can be useful for comparing large phylogenies, especially when some taxa are misplaced (e.g. due to horizontal gene transfer, recombination, or reconstruction errors).
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Xephon Technology Transfer Ltd., Maidenhead (UK) · OpenGrey (Institut de l'Information Scientifique et Technique) · 1983
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Kumar, Bheemaiah Anil K · Zenodo (CERN European Organization for Nuclear Research) · 2023
<em>Abstract: Spin Transfer Theory is a promising model for transferring quantum information between spin waves in a spin foam, and using this information to implement quantum computing devices. In this paper, we present a quantum computing perspective on Spin Transfer Theory, and describe how to implement computing devices using quantum circuits. We provide examples of circuits and their corresponding quantum lambdas, which describe the probability distribution of the output states given the input state. Our results demonstrate the potential of Spin Transfer Theory for implementing quantum computing devices.</em>
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Dr Bheemaiah Anil K Kumar · Zenodo (CERN European Organization for Nuclear Research) · 2023
<em>Abstract: Spin Transfer Theory is a promising model for transferring quantum information between spin waves in a spin foam, and using this information to implement quantum computing devices. In this paper, we present a quantum computing perspective on Spin Transfer Theory, and describe how to implement computing devices using quantum circuits. We provide examples of circuits and their corresponding quantum lambdas, which describe the probability distribution of the output states given the input state. Our results demonstrate the potential of Spin Transfer Theory for implementing quantum computing devices.</em>
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Lee, Seungwon, Von Allmen, Paul · NASA Technical Reports Server (NASA)
A package of software computes the time-dependent propagation of a narrow laser beam in an arbitrary three- dimensional (3D) medium with absorption and scattering, using the transient-discrete-ordinates method and a direct integration method. Unlike prior software that utilizes a Monte Carlo method, this software enables simulation at very small signal-to-noise ratios. The ability to simulate propagation of a narrow laser beam in a 3D medium is an improvement over other discrete-ordinate software. Unlike other direct-integration software, this software is not limited to simulation of propagation of thermal radiation with broad angular spread in three dimensions or of a laser pulse with narrow angular spread in two dimensions. Uses for this software include (1) computing scattering of a pulsed laser beam on a material having given elastic scattering and absorption profiles, and (2) evaluating concepts for laser-based instruments for sensing oceanic turbulence and related measurements of oceanic mixed-layer depths. With suitable augmentation, this software could be used to compute radiative transfer in ultrasound imaging in biological tissues, radiative transfer in the upper Earth crust for oil exploration, and propagation of laser pulses in telecommunication applications.
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M. Venturiniy, A. Dragt · 2016
In many cases the most accurate information about fields in a magnet comes either from direct measurement (using for example spinning coils) or from a numerical computa-tion done with a 3D electromagnetic code. In this paper we show how this information can be used to compute transfer maps with high accuracy. The resulting transfer maps take into account all effects of real beamline elements includ-ing fringe-field and multipole error effects. The method we employ automatically incorporates the smoothing proper-ties of the Laplace Green function. Consequently, it is ro-bust against both measurement and electromagnetic code errors. The method has been implemented in the code MARYLIE as a pair of user–defined routines. 1
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Nikolay Yudin · Zenodo (CERN European Organization for Nuclear Research) · 2025
We investigate whether semantic knowledge can be transferred between neural net- work architectures using Hyperdimensional Computing (HDC) with ternary quantization. Through experiments on sentiment and topic classification tasks, we observe that cross- architecture transfer achieves 94–99% efficiency relative to student model ceilings when using contrastive alignment. In our experimental setup, we find that teacher model size did not correlate with transfer quality—a 66M parameter model achieved comparable or better results than models up to 14B parameters. These observations suggest that, at least for the tasks and configurations we tested, distributed AI systems may achieve effective knowledge sharing without requiring massive centralized models.
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Romeu Miquéias Szmoski, Fabiano Alan Serafim Ferrari, Sandro Ely de Souza Pinto et al. · Physics Letters A · 2013
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Nikolay Yudin · Zenodo (CERN European Organization for Nuclear Research) · 2025
We investigate whether semantic knowledge can be transferred between neural net- work architectures using Hyperdimensional Computing (HDC) with ternary quantization. Through experiments on sentiment and topic classification tasks, we observe that cross- architecture transfer achieves 94–99% efficiency relative to student model ceilings when using contrastive alignment. In our experimental setup, we find that teacher model size did not correlate with transfer quality—a 66M parameter model achieved comparable or better results than models up to 14B parameters. These observations suggest that, at least for the tasks and configurations we tested, distributed AI systems may achieve effective knowledge sharing without requiring massive centralized models.
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Zi-Yu Xia · Journal of Applied Mathematics and Physics · 2022
I propose a new algorithm that uses recursive relations to compute spectroscopic factor, pair transfer amplitude and cluster transfer amplitude. I demonstrate the algorithm that it can be calculated very quickly and stored within small computer memory consumption. In BCS case, the particle number is always conserved and the time-consuming projection is avoided. I drive analytical expressions for the pair transfer amplitude and the cluster transfer amplitude expressed by asymmetry many-pair density matrix. This algorithm practically could be used in all of the nuclear double beta decay fields, the heavy cluster emission fields and the single-nucleon transfer of the odd-mass isotopes.
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