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Raquibuzzaman, Md, Aleksandar Milenkovic, and Biswajit Ray. "EXPRESS: Exploiting Energy–Accuracy Tradeoffs in 3D NAND Flash Memory for Energy-Efficient Storage." Electronics 11, no. 3 (January 30, 2022): 424. http://dx.doi.org/10.3390/electronics11030424.
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The density and cost-effectiveness of flash memory chips continue to increase, driven by: (a) The continuous physical scaling of memory cells in a single layer; (b) The vertical stacking of multiple layers; and (c) Logical scaling through storing multiple bits of information in a single memory cell. The physical properties of flash memories impose disproportionate latency and energy expenditures to ensure the high integrity of the data during flash memory writes. This paper experimentally explores this disproportionality on state-of-the-art commercial 3D NAND flash memories and introduces EXPRESS—a technique for increasing the energy efficiency of flash memory writes by exploiting the premature termination of the flash write operations. An experimental evaluation shows that EXPRESS reduces energy expenditures by 20–50%, relative to the traditional flash writes, at the cost of a minimal loss in the data integrity (<1%). In addition, we evaluate the effects of the page-to-page variability, program–erase cycling, and data retention on the implementation of EXPRESS, and we propose enhancements to counter these effects.
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Jeong, Jonghyun, and Youngmin Kim. "ASAD-RD: Accuracy Scalable Approximate Divider Based on Restoring Division for Energy Efficiency." Electronics 10, no. 1 (December 28, 2020): 31. http://dx.doi.org/10.3390/electronics10010031.
Повний текст джерелаАнотація:
Approximate computing can considerably improve energy efficiency by mitigating the accuracy requirements of calculations in error resilient application programming, such as machine learning, audio–video signal processing, data mining, and search engines. In this study, we propose an approximate divider for dynamic energy-quality scaling, which involves a trade-off between accuracy and latency. Previous approximate dividers for dynamic energy-quality scaling are well-configured, but lack energy-quality scalability. The key is to create a more accurate dynamic approximate divider while extending the limits of accuracy to maximize energy efficiency and meet various accuracy requirements. The proposed divider, called the accuracy scalable approximate divider based on restoring division (ASAD-RD), uses restoring division to significantly improve the error of the approximate divider and to use less latency. For the 8-bit division, SAADI, the previous design, has an average accuracy of 90.78% to 98.77%; however, ASAD-RD can improve the accuracy between 95.2% and 99.23% and hardly requires additional power consumption. Furthermore, for the same target accuracy, ASAD-RD requires fewer cycle iterations than SAADI. Thus, ASAD-RD requires lower energy than SAADI and can operate as an energy-efficient approximate divider.
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Ghedini, Giulia, Martino E. Malerba, and Dustin J. Marshall. "How to estimate community energy flux? A comparison of approaches reveals that size-abundance trade-offs alter the scaling of community energy flux." Proceedings of the Royal Society B: Biological Sciences 287, no. 1933 (August 19, 2020): 20200995. http://dx.doi.org/10.1098/rspb.2020.0995.
Повний текст джерелаАнотація:
Size and metabolism are highly correlated, so that community energy flux might be predicted from size distributions alone. However, the accuracy of predictions based on interspecific energy–size relationships relative to approaches not based on size distributions is unknown. We compare six approaches to predict energy flux in phytoplankton communities across succession: assuming a constant energy use among species (per cell or unit biomass), using energy–size interspecific scaling relationships and species-specific rates (both with or without accounting for density effects). Except for the per cell approach, all others explained some variation in energy flux but their accuracy varied considerably. Surprisingly, the best approach overall was based on mean biomass-specific rates, followed by the most complex (species-specific rates with density). We show that biomass-specific rates alone predict community energy flux because the allometric scaling of energy use with size measured for species in isolation does not reflect the isometric scaling of these species in communities. We also find energy equivalence throughout succession, even when communities are not at carrying capacity. Finally, we discuss that species assembly can alter energy–size relationships, and that metabolic suppression in response to density might drive the allometry of community energy flux as biomass accumulates.
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Blažek, Mikuláš. "Multifractality in High Energy Collisions." Fractals 05, no. 02 (June 1997): 309–20. http://dx.doi.org/10.1142/s0218348x97000292.
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With increasing energy of nuclear collisions, several statistical distributions of produced particles show changes in shape. This also concerns the scaling indices which characterize multifractality in the observed particle density distributions. In the present contribution, the self-similar processes governing that multifractality are described in more detail. It is shown especially that the corresponding extended fundamental equation reproduces, with very good accuracy, the data resulting from the oxygen beam at 60 and 200 A GeV colliding with the emulsion nuclei. The approximate description of the quantities characterizing scaling properties near the quark-gluon phase transition is discussed too.
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Gebauer, Ralph, Morrel H. Cohen, and Roberto Car. "A well-scaling natural orbital theory." Proceedings of the National Academy of Sciences 113, no. 46 (November 1, 2016): 12913–18. http://dx.doi.org/10.1073/pnas.1615729113.
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We introduce an energy functional for ground-state electronic structure calculations. Its variables are the natural spin-orbitals of singlet many-body wave functions and their joint occupation probabilities deriving from controlled approximations to the two-particle density matrix that yield algebraic scaling in general, and Hartree–Fock scaling in its seniority-zero version. Results from the latter version for small molecular systems are compared with those of highly accurate quantum-chemical computations. The energies lie above full configuration interaction calculations, close to doubly occupied configuration interaction calculations. Their accuracy is considerably greater than that obtained from current density-functional theory approximations and from current functionals of the one-particle density matrix.
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Mikhalev, A., M. Nottoli, and B. Stamm. "Linearly scaling computation of ddPCM solvation energy and forces using the fast multipole method." Journal of Chemical Physics 157, no. 11 (September 21, 2022): 114103. http://dx.doi.org/10.1063/5.0104536.
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This paper proposes the first linear scaling implementation for the domain decomposition approach of the polarizable continuum model (ddPCM) for the computation of the solvation energy and forces. The ddPCM-equation consists of a (non-local) integral equation on the van der Waals or solvent accessible surface of the solute’s cavity resulting in a dense solution matrix, and, in turn, one matrix–vector multiplication has a quadratic arithmetic complexity with respect to the number of atoms of the solute molecule. The use of spherical harmonics as basis functions makes it natural to employ the fast multipole method (FMM) in order to provide an asymptotically linear scaling method. In this paper, we employ the FMM in a non-uniform manner with a clusterization based on a recursive inertial bisection. We present some numerical tests illustrating the accuracy and scaling of our implementation.
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Hassan, Salma, Sameh Attia, Khaled Nabil Salama, and Hassan Mostafa. "EANN: Energy Adaptive Neural Networks." Electronics 9, no. 5 (May 1, 2020): 746. http://dx.doi.org/10.3390/electronics9050746.
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This paper proposes an Energy Adaptive Feedforward Neural Network (EANN). It uses multiple approximation techniques in the hardware implementation of the neuron unit. The used techniques are precision scaling, approximate multiplier, computation skipping, neuron skipping, activation function approximation and truncated accumulation. The proposed EANN system applies the partial dynamic reconfiguration (PDR) feature supported by the FPGA platform to reconfigure the hardware elements of the neural network based on the energy budget. The PDR technique enables the EANN system to remain functioning when the available energy budget is reduced by factors of 46.2% to 79.8% of the total energy of the unapproximated neural network. Unlike the conventional operation that only uses certain amount of energy and cannot function properly if the energy budget falls below that energy level, the EANN system remains functioning for longer time after energy drop at the expense of less accuracy. The proposed EANN system is highly recommended in limited-energy applications as it adapts the hardware units to the degraded energy at the expense of some accuracy loss.
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Zhang, Dengyong, Xiao Chen, Feng Li, Arun Kumar Sangaiah, and Xiangling Ding. "Seam-Carved Image Tampering Detection Based on the Cooccurrence of Adjacent LBPs." Security and Communication Networks 2020 (December 21, 2020): 1–12. http://dx.doi.org/10.1155/2020/8830310.
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Seam carving has been widely used in image resizing due to its superior performance in avoiding image distortion and deformation, which can maliciously be used on purpose, such as tampering contents of an image. As a result, seam-carving detection is becoming crucially important to recognize the image authenticity. However, existing methods do not perform well in the accuracy of seam-carving detection especially when the scaling ratio is low. In this paper, we propose an image forensic approach based on the cooccurrence of adjacent local binary patterns (LBPs), which employs LBP to better display texture information. Specifically, a total of 24 energy-based, seam-based, half-seam-based, and noise-based features in the LBP domain are applied to the seam-carving detection. Moreover, the cooccurrence features of adjacent LBPs are combined to highlight the local relationship between LBPs. Besides, SVM after training is adopted for feature classification to determine whether an image is seam-carved or not. Experimental results demonstrate the effectiveness in improving the detection accuracy with respect to different scaling ratios, especially under low scaling ratios.
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Chafid, Much, Abdul Syukur, Moch Arief Soeleman, and Affandy Affandy. "Seam Cerving and Salient Detection for Thumbnail Photos." Journal of Development Research 6, no. 1 (May 31, 2022): 16–21. http://dx.doi.org/10.28926/jdr.v6i1.204.
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Image resizing is a process of processing images or images with the aim of changing the size of the image. The most commonly used methods are cropping or scaling. Scaling is changing the size of the image based on the scale. Contents in the image are not considered in scaling. Seam carving often uses energy functionality that is useful as a determinant of the pixel level contained in an image. Seam is a connecting path of image pixels both vertically and horizontally that is passed by a low energy function. Changing the image size using seam carving is considered better than cropping and scaling. However, the seam carving method still cannot protect the object that is considered the most important. In overcoming this weakness, we can use a combination of seam carving algorithm with salient detection. In this research, we will improve the two methods which function as thumbnail maker. The results of the salient detection of the most important areas of the image will be detected and as a reference in resizing the image (seam carving) The dataset uses 200 images. The accuracy value is calculated by distributing questionnaires to 100 respondents and producing an acceptance rate of 78% so that the results are Very Natural/Natural.
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Wright, Michael Dennis, Francesco Gambioli, and Arnaud George Malan. "CFD Based Non-Dimensional Characterization of Energy Dissipation Due to Verticle Slosh." Applied Sciences 11, no. 21 (November 5, 2021): 10401. http://dx.doi.org/10.3390/app112110401.
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We present the CFD based non-dimensional characterization of violent slosh induced energy dissipation due a tank under vertical excitation. Experimentally validated CFD is used for this purpose as an ideally suited and versatile tool. It is thus first demonstrated that a weakly compressible VoF based CFD scheme is capable of computing violent slosh induced energy dissipation with high accuracy. The resulting CFD based energy analysis further informs that the main source of energy dissipation during violent slosh is due liquid impact. Next, a functional relationship characterising slosh induced energy dissipation is formulated in terms of fluid physics based non-dimensional numbers. These comprised contact angle and liquid–gas density ratio as well as Reynolds, Weber and Froude numbers. The Froude number is found the most significant in characterising verticle violent slosh induced energy dissipation (in the absence of significant phase change). The validated CFD is consequently employed to develop scaling laws (curve fits) which quantify energy dissipation as a function of the most important fluid physics non-dimensional numbers. These newly developed scaling laws show for the first time that slosh induced energy dissipation may be expressed as a quadratic function of Froude number and as a linear function of liquid–gas density ratio. Based on the aforementioned it is postulated that violent slosh induced energy dissipation may be expressed as a linear function of tank kinetic energy. The article is concluded by demonstrating the practical use of the novel CFD derived non-dimensional scaling laws to infer slosh induced energy dissipation for ideal experiments (with exact fluid physics similarity to the full scale Aircraft) from (non-ideal) slosh experiments.
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CASTRO, FRANCISCO JOSÉ BRITO. "DISPERSION ANALYSIS OF AN ENERGY-ORTHOGONAL THIN PLATE FINITE ELEMENT." International Journal of Computational Methods 08, no. 03 (September 2011): 425–62. http://dx.doi.org/10.1142/s0219876211002642.
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This paper studies the propagation of plane harmonic waves in thin plates discretized by using a finite element where the stiffness matrix and the elastic energy are split into basic and higher-order components. These ones are obtained from constant and deviatoric curvature fields, respectively. Based on the properties of the higher-order energy, four reference frequencies are defined. Depending on the desired precision, one of those values is selected as optimum cutoff frequency to properly capture a wave field. A scaling coefficient multiplying the higher-order stiffness is updated in order to enhance the accuracy of the discretized model.
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Brissaud, Quentin, and Victor C. Tsai. "Validation of a fast semi-analytic method for surface-wave propagation in layered media." Geophysical Journal International 219, no. 2 (September 5, 2019): 1405–20. http://dx.doi.org/10.1093/gji/ggz351.
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SUMMARY Green’s functions provide an efficient way to model surface-wave propagation and estimate physical quantities for near-surface processes. Several surface-wave Green’s function approximations (far-field, no mode conversions and no higher mode surface waves) have been employed for numerous applications such as estimating sediment flux in rivers, determining the properties of landslides, identifying the seismic signature of debris flows or to study seismic noise through cross-correlations. Based on those approximations, simple empirical scalings exist to derive phase velocities and amplitudes for pure power-law velocity structures providing an exact relationship between the velocity model and the Green’s functions. However, no quantitative estimates of the accuracy of these simple scalings have been reported for impulsive sources in complex velocity structures. In this paper, we address this gap by comparing the theoretical predictions to high-order numerical solutions for the vertical component of the wavefield. The Green’s functions computation shows that attenuation-induced dispersion of phase and group velocity plays an important role and should be carefully taken into account to correctly describe how surface-wave amplitudes decay with distance. The comparisons confirm the general reliability of the semi-analytic model for power-law and realistic shear velocity structures to describe fundamental-mode Rayleigh waves in terms of characteristic frequencies, amplitudes and envelopes. At short distances from the source, and for large near-surface velocity gradients or high Q values, the low-frequency energy can be dominated by higher mode surface waves that can be captured by introducing additional higher mode Rayleigh-wave power-law scalings. We also find that the energy spectral density for realistic shear-velocity models close to piecewise power-law models can be accurately modelled using the same non-dimensional scalings. The frequency range of validity of each power-law scaling can be derived from the corresponding phase velocities. Finally, highly discontinuous near-surface velocity profiles can also be approximated by a combination of power-law scalings. Analytical Green’s functions derived from the non-dimensionalization provide a good estimate of the amplitude and variations of the energy distribution, although the predictions are quite poor around the frequency bounds of each power-law scaling.
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Shen, Zichao, Neil Howard, and Jose Nunez-Yanez. "Big–Little Adaptive Neural Networks on Low-Power Near-Subthreshold Processors." Journal of Low Power Electronics and Applications 12, no. 2 (May 18, 2022): 28. http://dx.doi.org/10.3390/jlpea12020028.
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This paper investigates the energy savings that near-subthreshold processors can obtain in edge AI applications and proposes strategies to improve them while maintaining the accuracy of the application. The selected processors deploy adaptive voltage scaling techniques in which the frequency and voltage levels of the processor core are determined at the run-time. In these systems, embedded RAM and flash memory size is typically limited to less than 1 megabyte to save power. This limited memory imposes restrictions on the complexity of the neural networks model that can be mapped to these devices and the required trade-offs between accuracy and battery life. To address these issues, we propose and evaluate alternative ‘big–little’ neural network strategies to improve battery life while maintaining prediction accuracy. The strategies are applied to a human activity recognition application selected as a demonstrator that shows that compared to the original network, the best configurations obtain an energy reduction measured at 80% while maintaining the original level of inference accuracy.
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Paul, Ankita, Md Abu Saleh Tajin, Anup Das, William M. Mongan, and Kapil R. Dandekar. "Energy-Efficient Respiratory Anomaly Detection in Premature Newborn Infants." Electronics 11, no. 5 (February 23, 2022): 682. http://dx.doi.org/10.3390/electronics11050682.
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Precise monitoring of respiratory rate in premature newborn infants is essential to initiating medical interventions as required. Wired technologies can be invasive and obtrusive to the patients. We propose a deep-learning-enabled wearable monitoring system for premature newborn infants, where respiratory cessation is predicted using signals that are collected wirelessly from a non-invasive wearable Bellypatch put on the infant’s body. We propose a five-stage design pipeline involving data collection and labeling, feature scaling, deep learning model selection with hyperparameter tuning, model training and validation, and model testing and deployment. The model used is a 1-D convolutional neural network (1DCNN) architecture with one convolution layer, one pooling layer, and three fully-connected layers, achieving 97.15% classification accuracy. To address the energy limitations of wearable processing, several quantization techniques are explored, and their performance and energy consumption are analyzed for the respiratory classification task. Results demonstrate a reduction of energy footprints and model storage overhead with a considerable degradation of the classification accuracy, meaning that quantization and other model compression techniques are not the best solution for respiratory classification problem on wearable devices. To improve accuracy while reducing the energy consumption, we propose a novel spiking neural network (SNN)-based respiratory classification solution, which can be implemented on event-driven neuromorphic hardware platforms. To this end, we propose an approach to convert the analog operations of our baseline trained 1DCNN to their spiking equivalent. We perform a design-space exploration using the parameters of the converted SNN to generate inference solutions having different accuracy and energy footprints. We select a solution that achieves an accuracy of 93.33% with 18x lower energy compared to the baseline 1DCNN model. Additionally, the proposed SNN solution achieves similar accuracy as the quantized model with a 4× lower energy.
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Geng, Chenhua, Hong-Ye Hu, and Yijian Zou. "Differentiable programming of isometric tensor networks." Machine Learning: Science and Technology 3, no. 1 (January 21, 2022): 015020. http://dx.doi.org/10.1088/2632-2153/ac48a2.
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Abstract Differentiable programming is a new programming paradigm which enables large scale optimization through automatic calculation of gradients also known as auto-differentiation. This concept emerges from deep learning, and has also been generalized to tensor network optimizations. Here, we extend the differentiable programming to tensor networks with isometric constraints with applications to multiscale entanglement renormalization ansatz (MERA) and tensor network renormalization (TNR). By introducing several gradient-based optimization methods for the isometric tensor network and comparing with Evenbly–Vidal method, we show that auto-differentiation has a better performance for both stability and accuracy. We numerically tested our methods on 1D critical quantum Ising spin chain and 2D classical Ising model. We calculate the ground state energy for the 1D quantum model and internal energy for the classical model, and scaling dimensions of scaling operators and find they all agree with the theory well.
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Träbert, Elmar. "Atomic Lifetime Data and Databases." Atoms 10, no. 2 (May 5, 2022): 46. http://dx.doi.org/10.3390/atoms10020046.
Повний текст джерелаАнотація:
Atomic-level lifetimes span a wide range, from attoseconds to years, relating to transition energy, multipole order, atomic core charge, relativistic effects, perturbation of atomic symmetries by external fields, and so on. Some parameters permit the application of simple scaling rules, others are sensitive to the environment. Which results deserve to be tabulated or stored in atomic databases? Which results require high accuracy to give insight into details of the atomic structure? Which data may be useful for the interpretation of plasma experiments or astrophysical observations without any particularly demanding accuracy threshold? Should computation on demand replace pre-fabricated atomic databases?
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Green, Sheldon, David L. Cochrane, and Donald G. Truhlar. "Accuracy of the energy‐corrected sudden (ECS) scaling procedure for rotational excitation of CO by collisions with Ar." Journal of Chemical Physics 84, no. 7 (April 1986): 3865–69. http://dx.doi.org/10.1063/1.450097.
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Onizawa, Naoya, Daisaku Katagiri, Kazumichi Matsumiya, Warren J. Gross, and Takahiro Hanyu. "An Accuracy/Energy-Flexible Configurable Gabor-Filter Chip Based on Stochastic Computation With Dynamic Voltage–Frequency–Length Scaling." IEEE Journal on Emerging and Selected Topics in Circuits and Systems 8, no. 3 (September 2018): 444–53. http://dx.doi.org/10.1109/jetcas.2018.2844329.
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Hu, Cheng, and Yuhui Deng. "Extracting a Credible Hint of Response Time to Scale Resources in Elastic Clusters." Journal of Circuits, Systems and Computers 29, no. 13 (February 24, 2020): 2050211. http://dx.doi.org/10.1142/s0218126620502114.
Повний текст джерелаАнотація:
In elastic clusters, the service resources (or called “resources” for short) can be dynamically scaled, thus providing opportunities to cut down the energy cost of redundant resources. Generally, taking into account the Quality of Service (QoS) of clusters, resources are carefully scaled according to specific hints which are some features of system status. However, when the Service Quality Requirement (SQR) is referred to the response time of requests, some widely used features cannot well reflect the status of the QoS. Consequently, the QoS cannot be well maintained, and the energy-saving efficiency is unsatisfactory. In this paper, we indicate that under such SQR, the outstanding hint for resource scaling is the response time of requests. Accordingly, we propose a resource scaling method which scales resources leveraging an elaborate Hint of Response time (HR). More specifically, HR is credible to foresee future QoS, and our method extracts HR by tracking and making analysis on the waiting requests in each server. Moreover, when resource scaling operation is performed, our method can estimate how many resources are suitable for current workloads with a good accuracy. Thereby, our method can timely and directly scale resources to the suitable amount, thus can significantly reduce the time delay of re-matching resources. Finally, our method can significantly promote cluster performance on both the QoS and the energy-saving efficiency.
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Skalidis, R., J. Sternberg, J. R. Beattie, V. Pavlidou, and K. Tassis. "Why take the square root? An assessment of interstellar magnetic field strength estimation methods." Astronomy & Astrophysics 656 (December 2021): A118. http://dx.doi.org/10.1051/0004-6361/202142045.
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Context. The magnetic field strength in interstellar clouds can be estimated indirectly from measurements of dust polarization by assuming that turbulent kinetic energy is comparable to the fluctuating magnetic energy, and using the spread of polarization angles to estimate the latter. The method developed by Davis (1951, Phys. Rev., 81, 890) and by Chandrasekhar and Fermi (1953, ApJ, 118, 1137) (DCF) assumes that incompressible magnetohydrodynamic (MHD) fluctuations induce the observed dispersion of polarization angles, deriving B ∝ 1∕δθ (or, equivalently, δθ ∝ MA, in terms of the Alfvénic Mach number). However, observations show that the interstellar medium is highly compressible. Recently, two of us (ST) relaxed the incompressibility assumption and derived instead B ∝ 1/√δθ (equivalently, δθ ∝ MA2). Aims. We explored what the correct scaling is in compressible and magnetized turbulence through theoretical arguments, and tested the assumptions and the accuracy of the two methods with numerical simulations. Methods. We used 26 magnetized, isothermal, ideal-MHD numerical simulations without self-gravity and with different types of forcing. The range of MA and sonic Mach numbers Ms explored are 0.1 ≤ MA ≤ 2.0 and 0.5 ≤ Ms ≤ 20. We created synthetic polarization maps and tested the assumptions and accuracy of the two methods. Results. The synthetic data have a remarkable consistency with the δθ ∝ MA2 scaling, which is inferred by ST, while the DCF scaling failed to follow the data. Similarly, the assumption of ST that the turbulent kinetic energy is comparable to the root-mean-square (rms) of the coupling term of the magnetic energy between the mean and fluctuating magnetic field is valid within a factor of two for all MA (with the exception of solenoidally driven simulations at high MA, where the assumption fails by a factor of 10). In contrast, the assumption of DCF that the turbulent kinetic energy is comparable to the rms of the second-order fluctuating magnetic field term fails by factors of several to hundreds for sub-Alfvénic simulations. The ST method shows an accuracy better than 50% over the entire range of MA explored; DCF performs adequately only in the range of MA for which it has been optimized through the use of a “fudge factor”. For low MA, it is inaccurate by factors of tens, since it omits the magnetic energy coupling term, which is of first order and corresponds to compressible modes. We found no dependence of the accuracy of the two methods on Ms. Conclusions. The assumptions of the ST method reflect better the physical reality in clouds with compressible and magnetized turbulence, and for this reason the method provides a much better estimate of the magnetic field strength over the DCF method. Even in super-Alfvénic cases where DCF might outperform ST, the ST method still provides an adequate estimate of the magnetic field strength, while the reverse is not true.
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Jia, Yuru, Ruiliang Zhang, Xue Lv, Tao Zhang, and Zhengwu Fan. "Research on Temperature Control of Fuel-Cell Cooling System Based on Variable Domain Fuzzy PID." Processes 10, no. 3 (March 8, 2022): 534. http://dx.doi.org/10.3390/pr10030534.
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To ensure the energy conversion efficiency of a proton-exchange membrane fuel cell (PEMFC), it is necessary to establish a water-cooled cooling system to keep the inlet temperature of fuel-cell coolant and the temperature difference between the inlet and outlet temperature within the set range. First, a semi-empirical and semi-mechanism model was built in Simulink. Then, a variable-universe fuzzy PID controller was designed to adjust the quantization factor and scaling factor by scaling factor α1, α2 and β to improve the accuracy of the control results. Finally, the cooling system model with controller is simulated. The results show that compared with other control methods, the simulation results of the variable-universe fuzzy PID controller have smaller maximum overshoot, faster response speed and more gentle temperature fluctuation.
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Belleflamme, Fabian, Anna-Sophia Hehn, Marcella Iannuzzi, and Jürg Hutter. "A variational formulation of the Harris functional as a correction to approximate Kohn–Sham density functional theory." Journal of Chemical Physics 158, no. 5 (February 7, 2023): 054111. http://dx.doi.org/10.1063/5.0122671.
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Accurate descriptions of intermolecular interactions are of great importance in simulations of molecular liquids. We present an electronic structure method that combines the accuracy of the Harris functional approach with the computational efficiency of approximately linear-scaling density functional theory (DFT). The non-variational nature of the Harris functional has been addressed by constructing a Lagrangian energy functional, which restores the variational condition by imposing stationarity with respect to the reference density. The associated linear response equations may be treated with linear-scaling efficiency in an atomic orbital based scheme. Key ingredients to describe the structural and dynamical properties of molecular systems are the forces acting on the atoms and the stress tensor. These first-order derivatives of the Harris Lagrangian have been derived and implemented in consistence with the energy correction. The proposed method allows for simulations with accuracies close to the Kohn–Sham DFT reference. Embedded in the CP2K program package, the method is designed to enable ab initio molecular dynamics simulations of molecular solutions for system sizes of several thousand atoms. Available subsystem DFT methods may be used to provide the reference density required for the energy correction at near linear-scaling efficiency. As an example of production applications, we applied the method to molecular dynamics simulations of the binary mixtures cyclohexane-methanol and toluene-methanol, performed within the isobaric-isothermal ensemble, to investigate the hydrogen bonding network in these non-ideal mixtures.
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Chuang, Man-Tsai, Yi-Hua Liu, and Song-Pei Ye. "A Novel Variable Step Size Incremental Conductance Method with an Adaptive Scaling Factor." Applied Sciences 10, no. 15 (July 29, 2020): 5214. http://dx.doi.org/10.3390/app10155214.
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In this paper, a novel variable step size (VSS) incremental conductance (INC) method with an adaptive scaling factor is proposed. The proposed technique utilizes the model-based state estimation method to calculate the irradiance level and then determine an appropriate scaling factor accordingly to enhance the capability of maximum power point tracking (MPPT). The fast and accurate tracking can be achieved by the presented method without the need for extra irradiance and temperature sensors. Only the voltage-and-current sets of any two operating points on the characteristic curve are needed to estimate the irradiance level. By choosing a proper scaling factor, the performance of the conventional VSS INC method can be improved. To validate the studied algorithm, a 600 W prototyping circuit is constructed and the performances are demonstrated experimentally. Compared to conventional VSS INC methods under the tested conditions, the tracking time is shortened by 31.8%. The tracking accuracy is also improved by 2.1% and 3.5%, respectively. Besides, tracking energy loss is reduced by 43.9% and 29.9%, respectively.
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Salvati, Laura, Marian Douspis, and Nabila Aghanim. "Impact of systematics on cosmological parameters from future galaxy cluster surveys." Astronomy & Astrophysics 643 (October 27, 2020): A20. http://dx.doi.org/10.1051/0004-6361/202038465.
Повний текст джерелаАнотація:
Galaxy clusters are a recent cosmological probe. The precision and accuracy of the cosmological parameters inferred from these objects are affected by the knowledge of cluster physics, entering the analysis through the mass-observable scaling relations, and the theoretical description of their mass and redshift distribution, modelled by the mass function. In this work we forecast the impact of different modelling of these ingredients for clusters detected by future optical and near-IR surveys. We consider the standard cosmological scenario and the case with a time-dependent equation of state for dark energy. We analyse the effect of increasing precision on the scaling relation calibration, finding improved constraints on the cosmological parameters. This higher precision exposes the impact of the mass function evaluation, which is a subdominant source of systematics for current data. We compare two different evaluations for the mass function. In both cosmological scenarios the use of different mass functions leads to biases in the parameter constraints. For the ΛCDM model, we find a 1.6σ shift in the (Ωm, σ8) parameter plane and a discrepancy of ∼7σ for the redshift evolution of the scatter of the scaling relations. For the scenario with a time-evolving dark energy equation of state, the assumption of different mass functions results in a ∼8σ tension in the w0 parameter. These results show the impact, and the necessity for a precise modelling, of the interplay between the redshift evolution of the mass function and of the scaling relations in the cosmological analysis of galaxy clusters.
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Chahal, Ayushi, Preeti Gulia, Nasib Singh Gill, and Jyotir Moy Chatterjee. "Performance Analysis of an Optimized ANN Model to Predict the Stability of Smart Grid." Complexity 2022 (August 3, 2022): 1–13. http://dx.doi.org/10.1155/2022/7319010.
Повний текст джерелаАнотація:
The stability of the power grid is concernment due to the high demand and supply to smart cities, homes, factories, and so on. Different machine learning (ML) and deep learning (DL) models can be used to tackle the problem of stability prediction for the energy grid. This study elaborates on the necessity of IoT technology to make energy grid networks smart. Different prediction models, namely, logistic regression, naïve Bayes, decision tree, support vector machine, random forest, XGBoost, k-nearest neighbor, and optimized artificial neural network (ANN), have been applied on openly available smart energy grid datasets to predict their stability. The present article uses metrics such as accuracy, precision, recall, f1-score, and ROC curve to compare different predictive models. Data augmentation and feature scaling have been applied to the dataset to get better results. The augmented dataset provides better results as compared with the normal dataset. This study concludes that the deep learning predictive model ANN optimized with Adam optimizer provides better results than other predictive models. The ANN model provides 97.27% accuracy, 96.79% precision, 95.67% recall, and 96.22% F1 score.
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Basu, Sukanta, Jean-François Vinuesa, and Andrew Swift. "Dynamic LES Modeling of a Diurnal Cycle." Journal of Applied Meteorology and Climatology 47, no. 4 (April 1, 2008): 1156–74. http://dx.doi.org/10.1175/2007jamc1677.1.
Повний текст джерелаАнотація:
Abstract The diurnally varying atmospheric boundary layer observed during the Wangara (Australia) case study is simulated using the recently proposed locally averaged scale-dependent dynamic subgrid-scale (SGS) model. This tuning-free SGS model enables one to dynamically compute the Smagorinsky coefficient and the subgrid-scale Prandtl number based on the local dynamics of the resolved velocity and temperature fields. It is shown that this SGS-model-based large-eddy simulation (LES) has the ability to faithfully reproduce the characteristics of observed atmospheric boundary layers even with relatively coarse resolutions. In particular, the development, magnitude, and location of an observed nocturnal low-level jet are depicted quite well. Some well-established empirical formulations (e.g., mixed layer scaling, spectral scaling) are recovered with good accuracy by this SGS parameterization. The application of this new-generation dynamic SGS modeling approach is also briefly delineated to address several practical wind-energy-related issues.
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JAIMUNGAL, S., M. H. S. AMIN, and G. ROSE. "PERSISTENT CURRENTS IN MESOSCOPIC RINGS AND BOUNDARY CONFORMAL FIELD THEORY." International Journal of Modern Physics B 13, no. 27 (October 30, 1999): 3171–81. http://dx.doi.org/10.1142/s0217979299002939.
Повний текст джерелаАнотація:
A tight-binding model of electron dynamics in mesoscopic normal rings is studied using boundary conformal field theory. The partition function is calculated in the low energy limit and the persistent current generated as a function of an external magnetic flux threading the ring is found. We study the cases where there are defects and electron–electron interactions separately. The same temperature scaling for the persistent current is found in each case and the functional form can be fitted, with a high degree of accuracy, to experimental data.
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Li, Anran, Wenfeng Gao, and Tao Liu. "Bulk Scaling Model of Entrainment Zone Thickness in a Convective Boundary Layer, with a Shear Effect Promoted by Velocity Difference." Atmosphere 11, no. 1 (January 3, 2020): 63. http://dx.doi.org/10.3390/atmos11010063.
Повний текст джерелаАнотація:
Studying the thickness of the convective boundary layer (CBL) is helpful for understanding atmospheric structure and the diffusion of air pollutants. When there is velocity shear in CBL, the flow field structure is very different from that of shear-free CBL, which makes the thickness model of the entrainment zone deviate. A large-eddy simulation (LES) approach is carried out for a horizontally homogeneous, atmospheric CBL, with a shear effect promoted by velocity difference to explore the bulk scaling model of the entrainment zone thickness. The post-processed data indicate that the existing bulk scaling models cannot synthetically represent the effects of shear and buoyancy on entrainment, resulting in reduced accuracy or limited applicability. Based on the fraction of turbulent kinetic energy (TKE) used for entrainment, a different form of the characteristic velocity scale, which includes the shear effect, is proposed, and a modified bulk scaling model that uses a potential temperature gradient to replace the potential temperature jump across the entrainment zone is constructed with the numerical results. The new model is found to provide an improved prediction of the entrainment zone thickness in a sheared CBL.
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Kitsios, Vassili, Jorgen S. Frederiksen, and Meelis J. Zidikheri. "Theoretical comparison of subgrid turbulence in atmospheric and oceanic quasi-geostrophic models." Nonlinear Processes in Geophysics 23, no. 2 (April 14, 2016): 95–105. http://dx.doi.org/10.5194/npg-23-95-2016.
Повний текст джерелаАнотація:
Abstract. Due to the massive disparity between the largest and smallest eddies in the atmosphere and ocean, it is not possible to simulate these flows by explicitly resolving all scales on a computational grid. Instead the large scales are explicitly resolved, and the interactions between the unresolved subgrid turbulence and large resolved scales are parameterised. If these interactions are not properly represented then an increase in resolution will not necessarily improve the accuracy of the large scales. This has been a significant and long-standing problem since the earliest climate simulations. Historically subgrid models for the atmosphere and ocean have been developed in isolation, with the structure of each motivated by different physical phenomena. Here we solve the turbulence closure problem by determining the parameterisation coefficients (eddy viscosities) from the subgrid statistics of high-resolution quasi-geostrophic atmospheric and oceanic simulations. These subgrid coefficients are characterised into a set of simple unifying scaling laws, for truncations made within the enstrophy-cascading inertial range. The ocean additionally has an inverse energy cascading range, within which the subgrid model coefficients have different scaling properties. Simulations adopting these scaling laws are shown to reproduce the statistics of the reference benchmark simulations across resolved scales, with orders of magnitude improvement in computational efficiency. This reduction in both resolution dependence and computational effort will improve the efficiency and accuracy of geophysical research and operational activities that require data generated by general circulation models, including weather, seasonal, and climate prediction; transport studies; and understanding natural variability and extreme events.
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Kitsios, V., J. S. Frederiksen, and M. J. Zidikheri. "Theoretical comparison of subgrid turbulence in the atmosphere and ocean." Nonlinear Processes in Geophysics Discussions 2, no. 6 (December 10, 2015): 1675–704. http://dx.doi.org/10.5194/npgd-2-1675-2015.
Повний текст джерелаАнотація:
Abstract. Due to the massive disparity between the largest and smallest eddies in the atmosphere and ocean, it is not possible to simulate these flows by explicitly resolving all scales on a computational grid. Instead the large scales are explicitly resolved, and the interactions between the unresolved subgrid turbulence and large resolved scales are parameterised. If these interactions are not properly represented then an increase in resolution will not necessarily improve the accuracy of the large scales. This has been a significant and long standing problem since the earliest climate simulations. Historically subgrid models for the atmosphere and ocean have been developed in isolation, with the structure of each motivated by different physical phenomena. Here we solve the turbulence closure problem by determining the parameterisation coefficients (eddy viscosities) from the subgrid statistics of high resolution quasi-geostrophic atmospheric and oceanic simulations. These subgrid coefficients are characterised into a set of simple unifying scaling laws, for truncations made within the enstrophy cascading inertial range. The ocean additionally has an inverse energy cascading range, within which the subgrid model coefficients have alternative scaling properties. Simulations adopting these scaling laws are shown to reproduce the statistics of the reference benchmark simulations across resolved scales, with orders of magnitude improvement in computational efficiency. This reduction in both resolution dependence and computational effort will improve the efficiency and accuracy of geophysical research and operational activities that require data generated by general circulation models, including: weather, seasonal and climate prediction; transport studies; and understanding natural variability and extreme events.
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Gong, Yuezheng, and Yushun Wang. "An Energy-Preserving Wavelet Collocation Method for General Multi-Symplectic Formulations of Hamiltonian PDEs." Communications in Computational Physics 20, no. 5 (November 2016): 1313–39. http://dx.doi.org/10.4208/cicp.231014.110416a.
Повний текст джерелаАнотація:
AbstractIn this paper, we develop a novel energy-preserving wavelet collocation method for solving general multi-symplectic formulations of Hamiltonian PDEs. Based on the autocorrelation functions of Daubechies compactly supported scaling functions, the wavelet collocation method is conducted for spatial discretization. The obtained semi-discrete system is shown to be a finite-dimensional Hamiltonian system, which has an energy conservation law. Then, the average vector field method is used for time integration, which leads to an energy-preserving method for multi-symplectic Hamiltonian PDEs. The proposed method is illustrated by the nonlinear Schrödinger equation and the Camassa-Holm equation. Since differentiation matrix obtained by the wavelet collocation method is a cyclic matrix, we can apply Fast Fourier transform to solve equations in numerical calculation. Numerical experiments show the high accuracy, effectiveness and conservation properties of the proposed method.
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Haussmann, Marc, Stephan Simonis, Hermann Nirschl, and Mathias J. Krause. "Direct numerical simulation of decaying homogeneous isotropic turbulence — numerical experiments on stability, consistency and accuracy of distinct lattice Boltzmann methods." International Journal of Modern Physics C 30, no. 09 (September 2019): 1950074. http://dx.doi.org/10.1142/s0129183119500748.
Повний текст джерелаАнотація:
Stability, consistency and accuracy of various lattice Boltzmann schemes are investigated by means of numerical experiments on decaying homogeneous isotropic turbulence (DHIT). Therefore, the Bhatnagar–Gross–Krook (BGK), the entropic lattice Boltzmann (ELB), the two-relaxation-time (TRT), the regularized lattice Boltzann (RLB) and the multiple-relaxation-time (MRT) collision schemes are applied to the three-dimensional Taylor–Green vortex, which represents a benchmark case for DHIT. The obtained turbulent kinetic energy, the energy dissipation rate and the energy spectrum are compared to reference data. Acoustic and diffusive scaling is taken into account to determine the impact of the lattice Mach number. Furthermore, three different Reynolds numbers [Formula: see text], [Formula: see text] and [Formula: see text] are considered. BGK shows instabilities, when the mesh is highly underresolved. The diverging simulations for MRT are ascribed to a strong lattice Mach number dependency. Despite the fact that the ELB modifies the bulk viscosity, it does not mimic a turbulence model. Therefore, no significant increase of stability in comparison to BGK is observed. The TRT “magic parameter” for DHIT at moderate Reynolds numbers is estimated with respect to the energy contribution. Stability and accuracy of the TRT scheme is found to be similar to BGK. For small lattice Mach numbers, the RLB scheme exhibits lowered energy contribution in the dissipation range compared to an analytical model spectrum. Overall, to enhance stability and accuracy, the lattice Mach number should be chosen with respect to the applied collision scheme.
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MA, DA-ZHU, XIN WU, and FU-YAO LIU. "VELOCITY CORRECTIONS TO KEPLER ENERGY AND LAPLACE INTEGRAL." International Journal of Modern Physics C 19, no. 09 (September 2008): 1411–24. http://dx.doi.org/10.1142/s0129183108012996.
Повний текст джерелаАнотація:
For each celestial body of multi-planet systems, there are two slowly varying quantities or quasi-integrals, Kepler energy and Laplace integral, which are closely associated with the orbital semimajor axis and eccentricity, respectively. To correct numerical errors of the quantities, we give an extension of Nacozy's approach and develop a new manifold correction method, where corresponding reference values of the quantities at every integration step are obtained from integral invariant relations, and only velocity corrections are used to approximately satisfy the two quasi-integrals. As a result, the scheme does enhance the quality of the integration by significantly raising the accuracy of the two elements. Especially, it is superior to the existing dual scaling method in the improvement of eccentricity in general when the adopted integrator provides a sufficient precision to the eccentricity.
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Huo, Qiang, Yiming Yang, Yiming Wang, Dengyun Lei, Xiangqu Fu, Qirui Ren, Xiaoxin Xu, et al. "A computing-in-memory macro based on three-dimensional resistive random-access memory." Nature Electronics 5, no. 7 (July 2022): 469–77. http://dx.doi.org/10.1038/s41928-022-00795-x.
Повний текст джерелаАнотація:
AbstractNon-volatile computing-in-memory macros that are based on two-dimensional arrays of memristors are of use in the development of artificial intelligence edge devices. Scaling such systems to three-dimensional arrays could provide higher parallelism, capacity and density for the necessary vector–matrix multiplication operations. However, scaling to three dimensions is challenging due to manufacturing and device variability issues. Here we report a two-kilobit non-volatile computing-in-memory macro that is based on a three-dimensional vertical resistive random-access memory fabricated using a 55 nm complementary metal–oxide–semiconductor process. Our macro can perform 3D vector–matrix multiplication operations with an energy efficiency of 8.32 tera-operations per second per watt when the input, weight and output data are 8, 9 and 22 bits, respectively, and the bit density is 58.2 bit µm–2. We show that the macro offers more accurate brain MRI edge detection and improved inference accuracy on the CIFAR-10 dataset than conventional methods.
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Shi, Yongtao, Xiaodong Zhao, Fan Zhang, and Yaguang Kong. "Non-Intrusive Load Monitoring Based on Swin-Transformer with Adaptive Scaling Recurrence Plot." Energies 15, no. 20 (October 21, 2022): 7800. http://dx.doi.org/10.3390/en15207800.
Повний текст джерелаАнотація:
Non-Intrusive Load Monitoring (NILM) is an effective energy consumption analysis technology, which just requires voltage and current signals on the user bus. This non-invasive monitoring approach can clarify the working state of multiple loads in the building with fewer sensing devices, thus reducing the cost of energy consumption monitoring. In this paper, an NILM method combining adaptive Recurrence Plot (RP) feature extraction and deep-learning-based image recognition is proposed. Firstly, the time-series signal of current is transformed into a threshold-free RP in phase space to obtain the image features. The Euclidean norm in threshold-free RP is scaled exponentially according to the voltage and current correlation to reflect the working characteristics of different loads adaptively. Afterwards, the obtained adaptive RP features can be mapped into images using the corresponding pixel value. In the load identification stage, an advanced computer vision deep network, Hierarchical Vision Transformer using Shifted Windows (Swin-Transformer), is applied to identify the adaptive RP images. The proposed solution is extensively verified by four real, measured load signal datasets, including industrial and household power situations, covering single-phase and three-phase electrical signals. The numerical results demonstrate that the proposed NILM method based on the adaptive RP can effectively improve the accuracy of load detection.
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Lu, Yao, John Panneerselvam, Lu Liu, and Yan Wu. "RVLBPNN: A Workload Forecasting Model for Smart Cloud Computing." Scientific Programming 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/5635673.
Повний текст джерелаАнотація:
Given the increasing deployments of Cloud datacentres and the excessive usage of server resources, their associated energy and environmental implications are also increasing at an alarming rate. Cloud service providers are under immense pressure to significantly reduce both such implications for promoting green computing. Maintaining the desired level of Quality of Service (QoS) without violating the Service Level Agreement (SLA), whilst attempting to reduce the usage of the datacentre resources is an obvious challenge for the Cloud service providers. Scaling the level of active server resources in accordance with the predicted incoming workloads is one possible way of reducing the undesirable energy consumption of the active resources without affecting the performance quality. To this end, this paper analyzes the dynamic characteristics of the Cloud workloads and defines a hierarchy for the latency sensitivity levels of the Cloud workloads. Further, a novel workload prediction model for energy efficient Cloud Computing is proposed, named RVLBPNN (Rand Variable Learning Rate Backpropagation Neural Network) based on BPNN (Backpropagation Neural Network) algorithm. Experiments evaluating the prediction accuracy of the proposed prediction model demonstrate that RVLBPNN achieves an improved prediction accuracy compared to the HMM and Naïve Bayes Classifier models by a considerable margin.
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Erhard, Jannis, Steffen Fauser, Egor Trushin та Andreas Görling. "Scaled σ-functionals for the Kohn–Sham correlation energy with scaling functions from the homogeneous electron gas". Journal of Chemical Physics 157, № 11 (21 вересня 2022): 114105. http://dx.doi.org/10.1063/5.0101641.
Повний текст джерелаАнотація:
The recently introduced σ-functionals constitute a new type of functionals for the Kohn–Sham (KS) correlation energy. σ-Functionals are based on the adiabatic-connection fluctuation–dissipation theorem, are computationally closely related to the well-known direct random phase approximation (dRPA), and are formally rooted in many-body perturbation theory along the adiabatic connection. In σ-functionals, the function of the eigenvalues σ of the Kohn–Sham response matrix that enters the coupling constant and frequency integration in the dRPA is replaced by another function optimized with the help of reference sets of atomization, reaction, transition state, and non-covalent interaction energies. σ-Functionals are highly accurate and yield chemical accuracy of 1 kcal/mol in reaction or transition state energies, in main group chemistry. A shortcoming of σ-functionals is their inability to accurately describe processes involving a change of the electron number, such as ionizations or electron attachments. This problem is attributed to unphysical self-interactions caused by the neglect of the exchange kernel in the dRPA and σ-functionals. Here, we tackle this problem by introducing a frequency- and σ-dependent scaling of the eigenvalues σ of the KS response function that models the effect of the exchange kernel. The scaling factors are determined with the help of the homogeneous electron gas. The resulting scaled σ-functionals retain the accuracy of their unscaled parent functionals but in addition yield very accurate ionization potentials and electron affinities. Moreover, atomization and total energies are found to be exceptionally accurate. Scaled σ-functionals are computationally highly efficient like their unscaled counterparts.
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Menon, S. V. G. "Scaling of Phase Diagram and Critical Point Parameters in Liquid-Vapour Phase Transition of Metallic Fluids." Condensed Matter 6, no. 1 (January 28, 2021): 6. http://dx.doi.org/10.3390/condmat6010006.
Повний текст джерелаАнотація:
The first objective of this paper is to investigate the scaling behavior of liquid-vapor phase transition in FCC and BCCmetals starting from the zero-temperature four-parameter formula for cohesive energy. The effective potentials between the atoms in the solid are determined while using lattice inversion techniques as a function of scaling variables in the four-parameter formula. These potentials are split into repulsive and attractive parts, as per the Weeks–Chandler–Anderson prescription, and used in the coupling-parameter expansion for solving the Ornstein–Zernike equation that was supplemented with an accurate closure. Thermodynamic quantities obtained via the correlation functions are used in order to obtain critical point parameters and liquid-vapor phase diagrams. Their dependence on the scaling variables in the cohesive energy formula are also determined. An equally important second objective of the paper is to revisit coupling parameter expansion for solving the Ornstein–Zernike equation. The Newton–Armijo non-linear solver and Krylov-space based linear solvers are employed in this regard. These methods generate a robust algorithm that can be used to span the entire fluid region, except very low temperatures. The accuracy of the method is established by comparing the phase diagrams with those that were obtained via computer simulation. The avoidance of the ’no-solution-region’ of the Ornstein-Zernike equation in coupling-parameter expansion is also discussed. Details of the method and complete algorithm provided here would make this technique more accessible to researchers investigating the thermodynamic properties of one component fluids.
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Lee, J. H., J. P. Monty, J. Elsnab, A. Toffoli, A. V. Babanin, and A. Alberello. "Estimation of Kinetic Energy Dissipation from Breaking Waves in the Wave Crest Region." Journal of Physical Oceanography 47, no. 5 (May 2017): 1145–50. http://dx.doi.org/10.1175/jpo-d-16-0273.1.
Повний текст джерелаАнотація:
AbstractWave-induced turbulence due to breaking in the absence of surface shear stresses is investigated experimentally. A high-fidelity particle image velocimetry (PIV) technique is used to measure the turbulence near the water surface, inside the wave crests. The spatial velocity vector fields of the breaking waves acquired from PIV provide accurate vertical velocity profiles near the air–water interface, as well as wavenumber velocity spectra beneath the breaking waves at different depths. These velocity spectra exhibit a Kolmogorov interval at high wavenumbers, indicating the presence of isotropic turbulence and permitting an estimation of energy dissipation rates. The depth dependence of dissipation rates of the breaking waves generated in the laboratory shows a scaling similar to that found in wind-forced breaking waves in the field. A phase dependence in the dissipation rates of turbulence kinetic energy is also observed, which should be considered to improve the accuracy of the estimated and modeled wave energy dissipation.
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Brun, Allan Sacha. "Rotation and magnetism of solar-like stars: from scaling laws to spot-dynamos." Proceedings of the International Astronomical Union 9, S302 (August 2013): 114–25. http://dx.doi.org/10.1017/s1743921314001859.
Повний текст джерелаАнотація:
AbstractThe Sun is the archetype of magnetic star and its proximity coupled with very high accuracy observations has helped us understanding how solar-like stars (e.g with a convective envelope) redistribute angular momentum and generate a cyclic magnetic field. However most solar models have been so fine tuned that when they are applied to other solar-like stars the agreement with observations is not good enough. I will thus discuss, based on theoretical considerations and multi-D MHD stellar models, what can be considered as robust properties of solar-like star dynamics and magnetism and what is still speculative. I will derive scaling laws for differential rotation and magnetic energy as a function of stellar parameters, discuss recent results of stellar dynamo models and define the new concept of spot-dynamo, e.g. global dynamo that develops self-consistent magnetic buoyant structures that emerge at the surface.
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Yang, Chen, Cunbo Zhang, Congzhang Gao, Xuefeng Xu, Chengxin Yu, Shuaichuang Wang, Zhengfeng Fan, and Jie Liu. "Machine learning on the ignition threshold for inertial confinement fusion." Physics of Plasmas 29, no. 8 (August 2022): 082702. http://dx.doi.org/10.1063/5.0097554.
Повний текст джерелаАнотація:
In inertial confinement fusion, the ignition threshold factor (ITF), defined as the ratio of the available shell kinetic energy to the minimum ignition energy, is an important metric for quantifying how far an implosion is from its performance cliff. Traditional ITF research is based on analytical theories with explicit scaling laws and parameters obtained by numerically fitting simulation data. This present study uses machine learning (ML) methods to train implicit but more reliable ITF expressions. One-dimensional numerical simulations are used to develop a dataset with 20 000 targets, in which alpha particle heating magnifies the fusion yield by a factor of 6.5. These targets are defined as marginal ignition targets whose ITF equals unity. ML models such as neural networks, support vector machines, and Gaussian processes are trained to connect the minimum ignition velocity vigt with other implosion parameters, yielding an ML-based ITF of [Formula: see text], where vimp represents the implosion velocity. Then, these ML models are used to obtain curves of the ignition probability vs the ITF and improved ignition cliffs that show considerably better accuracy than traditional scaling laws, which are observed. The results demonstrate that ML methods have promising application prospects for quantifying ignition margins and can be useful in optimizing ignition target designs and practical implosion experiments.
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Kurgansky, M. V. "On statistical equilibrium in helical fluid flows." Nonlinear Processes in Geophysics 13, no. 2 (June 2, 2006): 161–66. http://dx.doi.org/10.5194/npg-13-161-2006.
Повний текст джерелаАнотація:
Abstract. The statistical mechanics of 3-D helical flows is re-examined for a continuum truncated at a top wavenumber. Based on the principle of equipartition of the flow enstrophy between helical modes, the emerging (i) energy spectrum law "–2" and (ii) formal mathematical analogy between the helicity and the thermodynamic entropy are discussed. It is noted that the "–2" scaling law is consistent with both spectral equilibrium and spectral cascade paradigms. In an attempt to apply the obtained results to a turbulent flow regime within the Earth's outer liquid core, where the net helicity of a turbulent flow component is presumably explained by Earth's rotation, it has been noticed that it is the energy spectral law "–1", but not "–2", which is likely realized there and within the logarithmic accuracy corresponds to the case of the velocity structure function [u(l)]2 independency on the spatial scale l, the latter is consistent with observations. It is argued that the "–1" scaling law can also be interpreted in terms of the spectral equilibrium and it is emphasized that the causes of the likely dominance of the spectral law "–1" over the spectral law "–2" in this geophysical application deserve further investigation and clarification.
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Silva, Vitor Ramos Gomes da, Carlos Valderrama, Pierre Manneback, and Samuel Xavier-de-Souza. "Analytical Energy Model Parametrized by Workload, Clock Frequency and Number of Active Cores for Share-Memory High-Performance Computing Applications." Energies 15, no. 3 (February 7, 2022): 1213. http://dx.doi.org/10.3390/en15031213.
Повний текст джерелаАнотація:
Energy consumption is crucial in high-performance computing (HPC), especially to enable the next exascale generation. Hence, modern systems implement various hardware and software features for power management. Nonetheless, due to numerous different implementations, we can always push the limits of software to achieve the most efficient use of our hardware. To be energy efficient, the software relies on dynamic voltage and frequency scaling (DVFS), as well as dynamic power management (DPM). Yet, none have privileged information on the hardware architecture and application behavior, which may lead to energy-inefficient software operation. This study proposes analytical modeling for architecture and application behavior that can be used to estimate energy-optimal software configurations and provide knowledgeable hints to improve DVFS and DPM techniques for single-node HPC applications. Additionally, model parameters, such as the level of parallelism and dynamic power, provide insights into how the modeled application consumes energy, which can be helpful for energy-efficient software development and operation. This novel analytical model takes the number of active cores, the operating frequencies, and the input size as inputs to provide energy consumption estimation. We present the modeling of 13 parallel applications employed to determine energy-optimal configurations for several different input sizes. The results show that up to 70% of energy could be saved in the best scenario compared to the default Linux choice and 14% on average. We also compare the proposed model with standard machine-learning modeling concerning training overhead and accuracy. The results show that our approach generates about 10 times less energy overhead for the same level of accuracy.
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Matulis, A., J. O. Fjærestad, and K. A. Chao. "Electron Interaction in a Quantum Dot with Hard Wall Confinement Potential." International Journal of Modern Physics B 11, no. 08 (March 30, 1997): 1035–49. http://dx.doi.org/10.1142/s0217979297000538.
Повний текст джерелаАнотація:
We have investigated the electron interaction energy in a circular quantum dot with hard confinement potential, using a renormalized perturbation series (RPS) approach which interpolates between the perturbation solutions in the weak interaction regime and the asymptotic solutions in the strong interaction regime. The RPS is based on the scaling property of the Hamiltonian, and the numerical procedure is not complicated even when the number of electrons in the dot is not very small. The accuracy of the RPS calculation has been tested with two electrons in a dot, where the RPS ground state energy agrees with the exact numerical solution within 1% relative error. We have performed the RPS calculation for three and four electrons in the dot, from which the Coulomb charging energy is derived. The results suggest the potential application of pillar-shaped quantum dots for single-electron tunneling transistors operating at higher temperatures.
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HOLM, CHRISTIAN, та WOLFHARD JANKE. "HIGH-PRECISION MONTE CARLO DETERMINATION OF α/ν IN THE 3D CLASSICAL HEISENBERG MODEL". International Journal of Modern Physics C 05, № 02 (квітень 1994): 267–70. http://dx.doi.org/10.1142/s0129183194000295.
Повний текст джерелаАнотація:
To study the role of topological defects in the three-dimensional classical Heisenberg model we have simulated this model on simple cubic lattices of size up to 803, using the single-cluster Monte Carlo update. Analysing the specific-heat data of these simulations, we obtain a very accurate estimate for the ratio of the specific-heat exponent with the correlation-length exponent, α/ν, from a usual finite-size scaling analysis at the critical coupling Kc. Moreover, by fitting the energy at Kc, we reduce the error estimates by another factor of two, and get a value of α/ν, which is comparable in accuracy to best field theoretic estimates.
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Ben Meftah, Mouldi, Francesca De Serio, Diana De Padova, and Michele Mossa. "Hydrodynamic Structure with Scour Hole Downstream of Bed Sills." Water 12, no. 1 (January 9, 2020): 186. http://dx.doi.org/10.3390/w12010186.
Повний текст джерелаАнотація:
Experimental turbulence measurements of scour hole downstream of bed sills in alluvial channels with non-cohesive sediments are investigated. Using an Acoustic Doppler Velocimeter (ADV), the flow velocity-field within the equilibrium scour hole was comprehensively measured. In this study, we especially focus on the flow hydrodynamic structure in the scour hole at equilibrium. In addition to the flow velocity distribution in the equilibrium scour hole, the turbulence intensities, the Reynolds shear stresses, the turbulent kinetic energy, and the turbulent length scales are analyzed. Since the prediction of equilibrium scour features is always very uncertain, in this study and based on laboratory turbulence measurements, we apply the phenomenological theory of turbulence to predict the maximum equilibrium scour depth. With this approach, we obtain a new scaling of the maximum scour depth at equilibrium, which is validated using experimental data, satisfying the validity of a spectral exponent equal to −5/3. The proposed scaling shows a quite reasonable accuracy in predicting the equilibrium scour depth in different hydraulic structures.
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Bíró, Gábor, Gergely Gábor Barnaföldi, Tamás Sándor Biró, and Keming Shen. "Mass hierarchy and energy scaling of the Tsallis – Pareto parameters in hadron productions at RHIC and LHC energies." EPJ Web of Conferences 171 (2018): 14008. http://dx.doi.org/10.1051/epjconf/201817114008.
Повний текст джерелаАнотація:
The latest, high-accuracy identified hadron spectra measurements in highenergy nuclear collisions led us to the investigation of the strongly interacting particles and collective effects in small systems. Since microscopical processes result in a statistical Tsallis – Pareto distribution, the fit parameters q and T are well suited for identifying system size scalings and initial conditions. Moreover, parameter values provide information on the deviation from the extensive, Boltzmann – Gibbs statistics in finite-volumes. We apply here the fit procedure developed in our earlier study for proton-proton collisions [1, 2]. The observed mass and center-of-mass energy trends in the hadron production are compared to RHIC dAu and LHC pPb data in different centrality/multiplicity classes. Here we present new results on mass hierarchy in pp and pA from light to heavy hadrons.
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Martinez, R. Z., J. L. Domenech, D. Bermejo, F. Thibault, J. P. Bouanich, and C. Boulet. "Close coupling calculations for rotational relaxation of CO in argon: Accuracy of energy corrected sudden scaling procedures and comparison with experimental data." Journal of Chemical Physics 119, no. 20 (November 22, 2003): 10563–74. http://dx.doi.org/10.1063/1.1620506.
Повний текст джерела
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Ding, Ming, Tianyu Wang, and Xudong Wang. "Establishing Smartphone User Behavior Model Based on Energy Consumption Data." ACM Transactions on Knowledge Discovery from Data 16, no. 2 (July 21, 2021): 1–40. http://dx.doi.org/10.1145/3461459.
Повний текст джерелаАнотація:
In smartphone data analysis, both energy consumption modeling and user behavior mining have been explored extensively, but the relationship between energy consumption and user behavior has been rarely studied. Such a relationship is explored over large-scale users in this article. Based on energy consumption data, where each users’ feature vector is represented by energy breakdown on hardware components of different apps, User Behavior Models (UBM) are established to capture user behavior patterns (i.e., app preference, usage time). The challenge lies in the high diversity of user behaviors (i.e., massive apps and usage ways), which leads to high dimension and dispersion of data. To overcome the challenge, three mechanisms are designed. First, to reduce the dimension, apps are ranked with the top ones identified as typical apps to represent all. Second, the dispersion is reduced by scaling each users’ feature vector with typical apps to unit ℓ 1 norm. The scaled vector becomes Usage Pattern, while the ℓ 1 norm of vector before scaling is treated as Usage Intensity. Third, the usage pattern is analyzed with a two-layer clustering approach to further reduce data dispersion. In the upper layer, each typical app is studied across its users with respect to hardware components to identify Typical Hardware Usage Patterns (THUP). In the lower layer, users are studied with respect to these THUPs to identify Typical App Usage Patterns (TAUP). The analytical results of these two layers are consolidated into Usage Pattern Models (UPM), and UBMs are finally established by a union of UPMs and Usage Intensity Distributions (UID). By carrying out experiments on energy consumption data from 18,308 distinct users over 10 days, 33 UBMs are extracted from training data. With the test data, it is proven that these UBMs cover 94% user behaviors and achieve up to 20% improvement in accuracy of energy representation, as compared with the baseline method, PCA. Besides, potential applications and implications of these UBMs are illustrated for smartphone manufacturers, app developers, network providers, and so on.
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Okabe, Takuya, and Jin Yoshimura. "Earthquake size: An example of a statistical distribution that lacks a well-defined mean." American Journal of Physics 90, no. 7 (July 2022): 501–5. http://dx.doi.org/10.1119/10.0010261.
Повний текст джерелаАнотація:
Power-law distributions are observed to describe many physical phenomena with remarkable accuracy. In some cases, the distribution gives no indication of a cutoff in the tail, which poses interesting theoretical problems, because its average is then infinite. It is also known that the averages of samples of such data do not approach a normal distribution, even if the sample size increases. These problems have previously been studied in the context of random walks. Here, we present another example in which the sample average increases with the sample size. In the Gutenberg–Richter law for earthquakes, we show that the cumulative energy released by earthquakes grows faster than linearly with time. Here, increasing the time span of observation corresponds to increasing the sample size. While the mean of released energy is not well defined, its distribution obeys a non-trivial scaling law.