scholarly journals Low frequency steady-state brain responses modulate large scale functional networks in a frequency-specific means

2015 ◽  
Vol 37 (1) ◽  
pp. 381-394 ◽  
Author(s):  
Yi-Feng Wang ◽  
Zhiliang Long ◽  
Qian Cui ◽  
Feng Liu ◽  
Xiu-Juan Jing ◽  
...  
Keyword(s):  
Steady State ◽  
Large Scale ◽  
Low Frequency ◽  
Functional Networks ◽  
Brain Responses

scholarly journals Experiment Investigation of Bistable Vibration Energy Harvesting with Random Wave Environment

2021 ◽  
Vol 11 (9) ◽  
pp. 3868
Author(s):  
Qiong Wu ◽  
Hairui Zhang ◽  
Jie Lian ◽  
Wei Zhao ◽  
Shijie Zhou ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Energy Harvesting ◽  
Cantilever Beam ◽  
Large Scale ◽  
Low Frequency ◽  
Vibration Energy ◽  
Random Wave ◽  
Periodic Signal ◽  
Vibration Energy Harvesting ◽  
Motion Activity

The energy harvested from the renewable energy has been attracting a great potential as a source of electricity for many years; however, several challenges still exist limiting output performance, such as the package and low frequency of the wave. Here, this paper proposed a bistable vibration system for harvesting low-frequency renewable energy, the bistable vibration model consisting of an inverted cantilever beam with a mass block at the tip in a random wave environment and also develop a vibration energy harvesting system with a piezoelectric element attached to the surface of a cantilever beam. The experiment was carried out by simulating the random wave environment using the experimental equipment. The experiment result showed a mass block’s response vibration was indeed changed from a single stable vibration to a bistable oscillation when a random wave signal and a periodic signal were co-excited. It was shown that stochastic resonance phenomena can be activated reliably using the proposed bistable motion system, and, correspondingly, large-scale bistable responses can be generated to realize effective amplitude enlargement after input signals are received. Furthermore, as an important design factor, the influence of periodic excitation signals on the large-scale bistable motion activity was carefully discussed, and a solid foundation was laid for further practical energy harvesting applications.

scholarly journals A Novel Methodology for Adaptive Coordination of Multiple Controllers in Electrical Grids

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1474
Author(s):  
Ruben Tapia-Olvera ◽  
Francisco Beltran-Carbajal ◽  
Antonio Valderrabano-Gonzalez ◽  
Omar Aguilar-Mejia
Keyword(s):  
Power Systems ◽  
Power System ◽  
Electric Power ◽  
Large Scale ◽  
Short Circuit ◽  
Dynamic Performance ◽  
Low Frequency ◽  
Electric Power System ◽  
Design Stage ◽  
Positive Interaction

This proposal is aimed to overcome the problem that arises when diverse regulation devices and controlling strategies are involved in electric power systems regulation design. When new devices are included in electric power system after the topology and regulation goals were defined, a new design stage is generally needed to obtain the desired outputs. Moreover, if the initial design is based on a linearized model around an equilibrium point, the new conditions might degrade the whole performance of the system. Our proposal demonstrates that the power system performance can be guaranteed with one design stage when an adequate adaptive scheme is updating some critic controllers’ gains. For large-scale power systems, this feature is illustrated with the use of time domain simulations, showing the dynamic behavior of the significant variables. The transient response is enhanced in terms of maximum overshoot and settling time. This is demonstrated using the deviation between the behavior of some important variables with StatCom, but without or with PSS. A B-Spline neural networks algorithm is used to define the best controllers’ gains to efficiently attenuate low frequency oscillations when a short circuit event is presented. This strategy avoids the parameters and power system model dependency; only a dataset of typical variable measurements is required to achieve the expected behavior. The inclusion of PSS and StatCom with positive interaction, enhances the dynamic performance of the system while illustrating the ability of the strategy in adding different controllers in only one design stage.

scholarly journals Optimizing the Frequency Capping: A Robust and Reliable Methodology to Define the Number of Ads to Maximize ROAS

2021 ◽  
Vol 11 (15) ◽  
pp. 6688
Author(s):  
Jesús Romero Leguina ◽  
Ángel Cuevas Rumin ◽  
Rubén Cuevas Rumin
Keyword(s):  
High Frequency ◽  
Large Scale ◽  
Low Frequency ◽  
Digital Marketing ◽  
Optimal Frequency ◽  
Novel Technique ◽  
Maximum Threshold

The goal of digital marketing is to connect advertisers with users that are interested in their products. This means serving ads to users, and it could lead to a user receiving hundreds of impressions of the same ad. Consequently, advertisers can define a maximum threshold to the number of impressions a user can receive, referred to as Frequency Cap. However, low frequency caps mean many users are not engaging with the advertiser. By contrast, with high frequency caps, users may receive many ads leading to annoyance and wasting budget. We build a robust and reliable methodology to define the number of ads that should be delivered to different users to maximize the ROAS and reduce the possibility that users get annoyed with the ads’ brand. The methodology uses a novel technique to find the optimal frequency capping based on the number of non-clicked impressions rather than the traditional number of received impressions. This methodology is validated using simulations and large-scale datasets obtained from real ad campaigns data. To sum up, our work proves that it is feasible to address the frequency capping optimization as a business problem, and we provide a framework that can be used to configure efficient frequency capping values.

Cyclic Breathing Simulations in Large Scale Models of the Lung Airway From the Oronasal Opening to the Terminal Bronchioles

2012 ◽  
Author(s):  
D. Keith Walters ◽  
Greg W. Burgreen ◽  
Robert L. Hester ◽  
David S. Thompson ◽  
David M. Lavallee ◽  
...  
Keyword(s):  
Steady State ◽  
Boundary Conditions ◽  
Large Scale ◽  
Whole Body ◽  
Patient Specific ◽  
Cfd Simulations ◽  
Reduced Order ◽  
Scale Models ◽  
Steady State Simulation ◽  
Conducting Zone

Computational fluid dynamics (CFD) simulations were performed for unsteady periodic breathing conditions, using large-scale models of the human lung airway. The computational domain included fully coupled representations of the orotracheal region and large conducting zone up to generation four (G4) obtained from patient-specific CT data, and the small conducting zone (to G16) obtained from a stochastically generated airway tree with statistically realistic geometrical characteristics. A reduced-order geometry was used, in which several airway branches in each generation were truncated, and only select flow paths were retained to G16. The inlet and outlet flow boundaries corresponded to the oronasal opening (superior), the inlet/outlet planes in terminal bronchioles (distal), and the unresolved airway boundaries arising from the truncation procedure (intermediate). The cyclic flow was specified according to the predicted ventilation patterns for a healthy adult male at three different activity levels, supplied by the whole-body modeling software HumMod. The CFD simulations were performed using Ansys FLUENT. The mass flow distribution at the distal boundaries was prescribed using a previously documented methodology, in which the percentage of the total flow for each boundary was first determined from a steady-state simulation with an applied flow rate equal to the average during the inhalation phase of the breathing cycle. The distal pressure boundary conditions for the steady-state simulation were set using a stochastic coupling procedure to ensure physiologically realistic flow conditions. The results show that: 1) physiologically realistic flow is obtained in the model, in terms of cyclic mass conservation and approximately uniform pressure distribution in the distal airways; 2) the predicted alveolar pressure is in good agreement with previously documented values; and 3) the use of reduced-order geometry modeling allows accurate and efficient simulation of large-scale breathing lung flow, provided care is taken to use a physiologically realistic geometry and to properly address the unsteady boundary conditions.

Separatrix crossing and large scale diffusion in low-frequency three-wave systems

1998 ◽  
Vol 58 (3) ◽  
pp. 3768-3776 ◽  
Author(s):  
B. Weyssow ◽  
J. D. Reuss ◽  
J. Misguich
Keyword(s):  
Large Scale ◽  
Low Frequency ◽  
Separatrix Crossing

The Research of Production Process Statistical Steady-State Based on the Hypothesis Test

2011 ◽  
Vol 314-316 ◽  
pp. 2433-2438
Author(s):  
Wei Zhi Wang
Keyword(s):  
Quality Control ◽  
Steady State ◽  
Production Process ◽  
Quantitative Method ◽  
Large Scale ◽  
Hypothesis Test ◽  
Influence Factors ◽  
Normal Operation ◽  
Scale Production ◽  
Large Scale Production

By only applying a after the event exam in the quality control of the batch production is not enough to meet the needs of modern large-scale production. To a certain extent, modern quality control is a dynamic process of the steady-state judge and adjustment. A simple and reliable steady-state judge rule and method is the premise to guarantee the normal operation. This paper provides a quantitative method to evaluate production process steady-state by analyzing influence factors based on mathematical statistics. The method is both suitable for simple production process and complex production process with sub-processes.

scholarly journals Historical drought patterns over Canada and their teleconnections with large-scale climate signals

2018 ◽  
Vol 22 (6) ◽  
pp. 3105-3124 ◽  
Author(s):  
Zilefac Elvis Asong ◽  
Howard Simon Wheater ◽  
Barrie Bonsal ◽  
Saman Razavi ◽  
Sopan Kurkute
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Low Frequency ◽  
Kendall Test ◽  
Wavelet Coherence ◽  
Climate Indices ◽  
Data Sets ◽  
Canadian Prairies ◽  
Agriculture Industry ◽  
Spatio Temporal

Abstract. Drought is a recurring extreme climate event and among the most costly natural disasters in the world. This is particularly true over Canada, where drought is both a frequent and damaging phenomenon with impacts on regional water resources, agriculture, industry, aquatic ecosystems, and health. However, nationwide drought assessments are currently lacking and impacted by limited ground-based observations. This study provides a comprehensive analysis of historical droughts over the whole of Canada, including the role of large-scale teleconnections. Drought events are characterized by the Standardized Precipitation Evapotranspiration Index (SPEI) over various temporal scales (1, 3, 6, and 12 consecutive months, 6 months from April to September, and 12 months from October to September) applied to different gridded monthly data sets for the period 1950–2013. The Mann–Kendall test, rotated empirical orthogonal function, continuous wavelet transform, and wavelet coherence analyses are used, respectively, to investigate the trend, spatio-temporal patterns, periodicity, and teleconnectivity of drought events. Results indicate that southern (northern) parts of the country experienced significant trends towards drier (wetter) conditions although substantial variability exists. Two spatially well-defined regions with different temporal evolution of droughts were identified – the Canadian Prairies and northern central Canada. The analyses also revealed the presence of a dominant periodicity of between 8 and 32 months in the Prairie region and between 8 and 40 months in the northern central region. These cycles of low-frequency variability are found to be associated principally with the Pacific–North American (PNA) and Multivariate El Niño/Southern Oscillation Index (MEI) relative to other considered large-scale climate indices. This study is the first of its kind to identify dominant periodicities in drought variability over the whole of Canada in terms of when the drought events occur, their duration, and how often they occur.

scholarly journals Nonlinear Steady-State Optimization of Large-Scale Gas Transmission Networks

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2832
Author(s):  
Andrzej J. Osiadacz ◽  
Małgorzata Kwestarz
Keyword(s):  
Steady State ◽  
Large Scale ◽  
Optimization Problem ◽  
Operating Cost ◽  
Network Efficiency ◽  
Major Objective ◽  
Transmission Networks ◽  
Sqp Method ◽  
Gas Network ◽  
Compressor Power

The major optimization problem of the gas transmission system is to determine how to operate the compressors in a network to deliver a given flow within the pressure bounds while using minimum compressor power (minimum fuel consumption or maximum network efficiency). Minimization of fuel usage is a major objective to control gas transmission costs. This is one of the problems that has received most of the attention from both practitioners and researchers because of its economic impact. The article describes the algorithm of steady-state optimization of a high-pressure gas network of any structure that minimizes the operating cost of compressors. The developed algorithm uses the “sequential quadratic programming (SQP)” method. The tests carried out on the real network segment confirmed the correctness of the developed algorithm and, at the same time, proved its computational efficiency. Computational results obtained with the SQP method demonstrate the viability of this approach.

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