scholarly journals Dielectric Spectroscopy Using Dual Reflection Analysis of TDR Signals

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1299 ◽  
Author(s):  
Yin Ngui ◽  
Chih-Ping Lin ◽  
Tsai-Jung Wu
Keyword(s):  
Dielectric Spectroscopy ◽  
Time Window ◽  
Waveform Inversion ◽  
Input Function ◽  
Time Domain Reflectometry ◽  
Effective Bandwidth ◽  
Model Free ◽  
Robust Model ◽  
Long Time ◽  
Apparent Dielectric Constant

Time-domain reflectometry (TDR) has been a powerful tool for measuring soil dielectric properties. Initiating from apparent dielectric constant ( K a ) measurement up until apparent and complex dielectric spectroscopies, the embedded information in the TDR signal can be extracted to inspire our understanding of the underlying dielectric behaviors. Multiple full waveform inversion techniques have been developed to extract complex dielectric permittivity (CDP) spectrum, but most of them involved prior knowledge of input function and tedious calibration. This rendered the field dielectric spectroscopy challenging and expensive to conduct. Dual reflection analysis (DRA) is proposed in this study to measure CDP spectrum from 10 MHz to 1 GHz. DRA is a simple, robust, model-free, and source-function free algorithm which requires minimal calibration effort. The theoretical framework of DRA is established and the necessary signal processing procedures are elaborated in this study. Eight materials with different dielectric characteristics are selected to evaluate DRA’s performance, by using both simulated and experimental signals. DRA is capable of measuring non-dispersive materials very well, whereas dispersive materials require the assistance of a long-time-window (LTW) extraction method to further extend the effective bandwidth. The DRA approach is suitable for field applications that can only record a limited amount of data points and in-situ dielectric spectroscopy.

Time Window from Visual Images to Visual Short-Term Memory: Consolidation or Integration?

2004 ◽  
Vol 51 (1) ◽  
pp. 45-51 ◽  
Author(s):  
Yuhong Jiang
Keyword(s):  
Short Term Memory ◽  
Time Window ◽  
Short Interval ◽  
Visual Images ◽  
Short Term ◽  
Temporal Window ◽  
Term Memory ◽  
Visual Short Term Memory ◽  
Probe Task ◽  
Long Time

Abstract. When two dot arrays are briefly presented, separated by a short interval of time, visual short-term memory of the first array is disrupted if the interval between arrays is shorter than 1300-1500 ms ( Brockmole, Wang, & Irwin, 2002 ). Here we investigated whether such a time window was triggered by the necessity to integrate arrays. Using a probe task we removed the need for integration but retained the requirement to represent the images. We found that a long time window was needed for performance to reach asymptote even when integration across images was not required. Furthermore, such window was lengthened if subjects had to remember the locations of the second array, but not if they only conducted a visual search among it. We suggest that a temporal window is required for consolidation of the first array, which is vulnerable to disruption by subsequent images that also need to be memorized.

Intelligent PD controller design for active suspension system based on robust model-free control strategy

2019 ◽  
Vol 233 (14) ◽  
pp. 4863-4880 ◽  
Author(s):  
Maroua Haddar ◽  
Riadh Chaari ◽  
S Caglar Baslamisli ◽  
Fakher Chaari ◽  
Mohamed Haddar
Keyword(s):  
Controller Design ◽  
Design Method ◽  
Active Suspension ◽  
Vehicle Speed ◽  
Pd Controller ◽  
Suspension Systems ◽  
Model Free ◽  
Robust Model ◽  
Road Disturbance ◽  
Model Free Control

A novel active suspension control design method is proposed for attenuating vibrations caused by road disturbance inputs in vehicle suspension systems. For the control algorithm, we propose an intelligent PD controller structure that effectively rejects online estimated disturbances. The main theoretical techniques used in this paper consist of an ultra-local model which replaces the mathematical model of quarter car system and a new algebraic estimator of unknown information. The measurement of only input and output variables of the plant is required for achieving the reference tracking task and the cancellation of unmodeled exogenous and endogenous perturbations such as roughness road variation, unpredictable variation of vehicle speed and load variation. The performance and robustness of the proposed active suspension algorithm are compared with ADRC control and LQR control. Numerical results are provided for showing the improvement of passenger comfort criteria with model-free control.

scholarly journals Sensitivity of the tropical stratospheric ozone response to the solar rotational cycle in observations and chemistry-climate model simulations

2017 ◽  
Author(s):  
Rémi Thiéblemont ◽  
Marion Marchand ◽  
Slimane Bekki ◽  
Sébastien Bossay ◽  
Franck Lefèvre ◽  
...  
Keyword(s):  
Solar Cycle ◽  
Climate Model ◽  
Time Window ◽  
Stratospheric Ozone ◽  
Spectral Irradiance ◽  
Naval Research ◽  
Solar Spectral Irradiance ◽  
Model Free ◽  
Ozone Sensitivity ◽  
Ensemble Mean

Abstract. The tropical stratospheric ozone response to solar UV variations associated with the rotational cycle (~ 27 days) is analysed using MLS satellite observations and numerical simulations from the LMDz-Reprobus chemistry-climate model. The model is used in two configurations, as a chemistry-transport model (CTM) where dynamics are nudged toward ERA-Interim reanalysis and as a chemistry-climate model (free-running) (CCM). An ensemble of five 17 year simulations (1991–2007) is performed with the CCM. All simulations are forced by reconstructed time-varying solar spectral irradiance from the Naval Research Laboratory Solar Spectral Irradiance model. We first examine the ozone response to the solar rotational cycle during two 3 year periods which correspond to the declining phases of solar cycle 22 (10/1991–09/1994) and solar cycle 23 (09/200408/2007) when the satellite ozone observations of the two Microwave Limb Sounders (MLS-UARS and MLS-Aura) are available. In the observations, during the first period, ozone and UV flux are found to be correlated between about 10 and 1 hPa with a maximum of 0.29 at ~ 5 hPa; the ozone sensitivity (% change in ozone for 1 % change in UV) peaks at ~ 0.4. Correlation during the second period is weaker and has a peak ozone sensitivity of only 0.2, possibly due to the fact that the solar forcing is weaker during that period. The CTM simulation reproduces most of these observed features, including the differences between the two periods. The CCM ensemble mean results comparatively show much smaller differences between the two periods, suggesting that the amplitude of the rotational ozone signal estimated from MLS observations or the CTM simulation is strongly influenced by other (non-solar) sources of variability, notably dynamics. The analysis of the ensemble of CCM simulations shows that the estimation of the ensemble mean ozone sensitivity does not vary significantly neither with the amplitude of the solar rotational fluctuations, nor with the size of the time window used for the ozone sensitivity retrieval. In contrast, the uncertainty of the ozone sensitivity estimate significantly increases during periods of decreasing amplitude of solar rotational fluctuations (also coinciding with minimum phases of the solar cycle), and for decreasing size of the time window analysis. We found that a minimum of 3 year and 10 year time window is needed for the 1σ uncertainty to drop below 50 % and 20 %, respectively. These uncertainty sources may explain some of the discrepancies found in previous estimates of the ozone response to the solar rotational cycle.

scholarly journals IMPACT OF UNCERTAINTIES IN MODEL FREE PARAMETERS AND SEA LEVEL RISE ON SHORELINE CHANGES: A 20-YEAR HINDCAST AT TRUC VERT BEACH, SW FRANCE

2020 ◽  
pp. 10
Author(s):  
Maurizio D'Anna ◽  
Deborah Idier ◽  
Bruno Castelle ◽  
Goneri Le Cozannet ◽  
Jeremy Rohmer ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Spatial Scales ◽  
High Energy ◽  
Potential Threat ◽  
Shoreline Evolution ◽  
Complex Processes ◽  
Model Free ◽  
Long Time ◽  
Sw France

Chronic erosion of sandy coasts is a continuous potential threat for the growing coastal communities worldwide. The prediction of shoreline evolution is therefore key issue for robust decision making worldwide, especially in the context of climate change. Shorelines respond to various complex processes interacting at several temporal and spatial scales, making shoreline reconstructions and predictions challenging and uncertain, especially on long time scales (e.g. decades or century). Despite the increasing progresses in addressing uncertainties related to the physics of Sea Level Rise, very little effort is made towards understanding and reducing the uncertainties related to wave driven coastal response. To fill this gap, we analyse the uncertainties associated with long-term (2 decades) modelling of the cross-shore transport dominated high-energy sandy coast around Truc Vert beach, SW France, which has been surveyed semi-monthly over the last 12 years.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/_NBJ2v-koMs

scholarly journals Evolution of andrenine bees reveals a long and complex history of faunal interchanges between the Americas during the Mesozoic and Cenozoic

2021 ◽  
Author(s):  
Kelli S Ramos ◽  
Aline C Martins ◽  
Gabriel A R Melo
Keyword(s):  
North America ◽  
South America ◽  
Time Window ◽  
Distributional Pattern ◽  
Long Distance ◽  
Early Diversification ◽  
Palearctic Region ◽  
Long Time ◽  
The Times ◽  
Dated Phylogeny

Bees are presumed to have arisen in the early to mid-Cretaceous coincident with the fragmentation of the southern continents and concurrently with the early diversification of the flowering plants. Among the main groups of bees, Andreninae sensu lato comprise about 3000 species widely distributed with greatest and disjunct diversity in arid areas of North America, South America, and the Palearctic region. Here, we present the first comprehensive dated phylogeny and historical biogeographic analysis for andrenine bees, including representatives of all currently recognized tribes. Our analyses rely on a dataset of 106 taxa and 7952 aligned nucleotide positions from one mitochondrial and six nuclear loci. Andreninae is strongly supported as a monophyletic group and the recovered phylogeny corroborates the commonly recognized clades for the group. Thus, we propose a revised tribal classification that is congruent with our phylogenetic results. The time-calibrated phylogeny and ancestral range reconstructions of Andreninae reveal a fascinating evolutionary history with Gondwana patterns that are unlike those observed in other subfamilies of bees. Andreninae arose in South America during the Late Cretaceous around 90 Million years ago (Ma) and the origin of tribes occurred through a relatively long time-window from this age to the Miocene. The early evolution of the main lineages took place in South America until the beginning of Paleocene with North American fauna origin from it and Palearctic from North America as results of multiple lineage interchanges between these areas by long-distance dispersal or hopping through landmass chains. Overall, our analyses provide strong evidence of amphitropical distributional pattern currently observed in Andreninae in the American continent as result at least three periods of possible land connections between the two American landmasses, much prior to the Panama Isthmus closure. The andrenine lineages reached the Palearctic region through four dispersal events from North America during the Eocene, late Oligocene and early Miocene, most probably via the Thulean Bridge. The few lineages with Afrotropical distribution likely originated from a Palearctic ancestral in the Miocene around 10 Ma when these regions were contiguous, and the Sahara Desert was mostly vegetated making feasible the passage by several organisms. Incursions of andrenine bees to North America and then onto the Old World are chronological congruent with distinct periods when open-vegetation habitats were available for trans-continental dispersal and at the times when aridification and temperature decline offered favorable circumstances for bee diversification.

scholarly journals Asymmetric Residual Neural Network for Accurate Human Activity Recognition

Information ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 203 ◽  
Author(s):  
Jun Long ◽  
Wuqing Sun ◽  
Zhan Yang ◽  
Osolo Ian Raymond
Keyword(s):  
Activity Recognition ◽  
Human Activity ◽  
Time Window ◽  
Research Problem ◽  
Human Activity Recognition ◽  
Sensor Data ◽  
Practical Applications ◽  
Long Time ◽  
Benchmark Datasets ◽  
High Level

Human activity recognition (HAR) using deep neural networks has become a hot topic in human–computer interaction. Machines can effectively identify human naturalistic activities by learning from a large collection of sensor data. Activity recognition is not only an interesting research problem but also has many real-world practical applications. Based on the success of residual networks in achieving a high level of aesthetic representation of automatic learning, we propose a novel asymmetric residual network, named ARN. ARN is implemented using two identical path frameworks consisting of (1) a short time window, which is used to capture spatial features, and (2) a long time window, which is used to capture fine temporal features. The long time window path can be made very lightweight by reducing its channel capacity, while still being able to learn useful temporal representations for activity recognition. In this paper, we mainly focus on proposing a new model to improve the accuracy of HAR. In order to demonstrate the effectiveness of the ARN model, we carried out extensive experiments on benchmark datasets (i.e., OPPORTUNITY, UniMiB-SHAR) and compared the results with some conventional and state-of-the-art learning-based methods. We discuss the influence of networks parameters on performance to provide insights about its optimization. Results from our experiments show that ARN is effective in recognizing human activities via wearable datasets.

scholarly journals RETRACTED ARTICLE: Estimation of the source process and forward simulation of long-period ground motion of the 2018 Hokkaido Eastern Iburi, Japan, earthquake

2019 ◽  
Vol 71 (1) ◽  
Author(s):  
Hisahiko Kubo ◽  
Asako Iwaki ◽  
Wataru Suzuki ◽  
Shin Aoi ◽  
Haruko Sekiguchi
Keyword(s):  
Ground Motion ◽  
Velocity Structure ◽  
Time Window ◽  
Waveform Inversion ◽  
Strong Motion ◽  
Source Model ◽  
Multiple Time ◽  
Velocity Models ◽  
Long Period ◽  
Slip Area

Abstract In this study, we investigate the source rupture process of the 2018 Hokkaido Eastern Iburi earthquake in Japan (MJMA 6.7) and how the ground motion can be reproduced using available source and velocity models. First, we conduct a multiple-time-window kinematic waveform inversion using strong-motion waveforms, which indicates that a large-slip area located at a depth of 25–30 km in the up-dip direction from the hypocenter was caused by a rupture propagating upward 6–12 s after its initiation. Moreover, the high-seismicity area of aftershocks did not overlap with the large-slip area. Subsequently, using the obtained source model and a three-dimensional velocity structure model, we conduct a forward long-period (< 0.5 Hz) ground-motion simulation. The simulation was able to reproduce the overall ground-motion characteristics in the sedimentary layers of the Ishikari Lowland.

Zygnematophyceae: from living algae collections to the establishment of future models

2020 ◽  
Vol 71 (11) ◽  
pp. 3296-3304
Author(s):  
Hong Zhou ◽  
Klaus von Schwartzenberg
Keyword(s):  
Model Organism ◽  
Past Research ◽  
Model Organisms ◽  
Current Status ◽  
Future Research ◽  
Suitable Model ◽  
Research Perspectives ◽  
Robust Model ◽  
Physiological Adaptations ◽  
Long Time

Abstract The class of conjugating green algae, Zygnematophyceae (Conjugatophyceae), is extremely rich in species and has attracted the interest of phycologists for a long time. It is now widely accepted that this class of charophyte algae holds a key position in the phylogenetic tree of streptophytes, where they represent the closest relatives to all land plants (embryophytes). It is increasingly evident that robust model plants that can be easily cultivated and genetically transformed are necessary to better understand the process of terrestrialization and the related molecular, cellular, and physiological adaptations. Living algae collections play an important role, not only for phylogenomic-based taxonomy but also for screening for suitable model organisms. For this review, we screened six major public algae collections for Zygnematophyceae strains and established a cumulative list comprising 738 different taxa (including species, subspecies, varieties, and forms). From the described biodiversity with 8883 registered taxa (AlgaeBase) the cultured Zygnematophyceae taxa worldwide cover only ~8.3%. We review the past research on this clade of algae and discuss it from the perspective of establishing a model organism. We present data on the life cycle of the genera Micrasterias and Spirogyra, representing the orders Desmidiales and Zygnematales, and outline the current status of genetic transformation of Zygnematophyceae algae and future research perspectives.

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