scholarly journals A Prediction-Based Model for Consistent Adaptive Routing in Back-Bone Networks at Extreme Situations

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2146
Author(s):  
Qianru Zhou ◽  
Dimitrios Pezaros
Keyword(s):  
Real Life ◽  
Adaptive Routing ◽  
Time Interval ◽  
Backbone Networks ◽  
Latency Difference ◽  
Congestion Prediction ◽  
Long Time ◽  
Parameter Values

To reduce congestion, numerous routing solutions have been proposed for backbone networks, but how to select paths that stay consistently optimal for a long time in extremely congested situations, avoiding the unnecessary path reroutings, has not yet been investigated much. To solve that issue, a model that can measure the consistency of path latency difference is needed. In this paper, we make a humble step towards a consistent differential path latency model and by predicting base on that model, a metric Path Swap Indicator (PSI) is proposed. By learning the history latency of all optional paths, PSI is able to predict the onset of an obvious and steady channel deterioration and make the decision to switch paths. The effect of PSI is evaluated from the following aspects: (1) the consistency of the path selected, by measuring the time interval between PSI changes; (2) the accuracy of the channel congestion situation prediction; and (3) the improvement of the congestion situation. Experiments were carried out on a testbed using real-life Abilene traffic datasets collected at different times and locations. Results show that the proposed PSI can stay consistent for over 1000 s on average, and more than 3000 s at the longest in our experiment, while at the same time achieving a congestion situation improvement of more than 300% on average, and more than 200% at the least. It is evident that the proposed PSI metric is able to provide a consistent channel congestion prediction with satisfiable channel improvement at the same time. The results also demonstrate how different parameter values impact the result, both in terms of prediction consistency and the congestion improvement.

An Adaptive and Learning System for Feedback-Controlled Evoked Response Studies

1981 ◽  
Vol 20 (03) ◽  
pp. 169-173
Author(s):  
J. Wagner ◽  
G. Pfurtscheixer
Keyword(s):  
Brain Activity ◽  
Evoked Response ◽  
Learning System ◽  
Time Interval ◽  
Electrical Brain Activity ◽  
Long Time ◽  
The Subject ◽  
Eeg Power ◽  
Stimulation System ◽  
Background Eeg

The shape, latency and amplitude of changes in electrical brain activity related to a stimulus (Evoked Potential) depend both on the stimulus parameters and on the background EEG at the time of stimulation. An adaptive, learnable stimulation system is introduced, whereby the subject is stimulated (e.g. with light), whenever the EEG power is subthreshold and minimal. Additionally, the system is conceived in such a way that a certain number of stimuli could be given within a particular time interval. Related to this time criterion, the threshold specific for each subject is calculated at the beginning of the experiment (preprocessing) and adapted to the EEG power during the processing mode because of long-time fluctuations and trends in the EEG. The process of adaptation is directed by a table which contains the necessary correction numbers for the threshold. Experiences of the stimulation system are reflected in an automatic correction of this table. Because the corrected and improved table is stored after each experiment and is used as the starting table for the next experiment, the system >learns<. The system introduced here can be used both for evoked response studies and for alpha-feedback experiments.

scholarly journals Optimal Perturbations of an Oceanic Vortex Lens

Fluids ◽  
2018 ◽  
Vol 3 (3) ◽  
pp. 63 ◽  
Author(s):  
Thomas Meunier ◽  
Claire Ménesguen ◽  
Xavier Carton ◽  
Sylvie Le Gentil ◽  
Richard Schopp
Keyword(s):  
Normal Mode ◽  
Growth Rates ◽  
Time Interval ◽  
Time Intervals ◽  
Horizontal Structure ◽  
Azimuthal Wave ◽  
Wave Numbers ◽  
Non Linear ◽  
Long Time ◽  
Short Time

The stability properties of a vortex lens are studied in the quasi geostrophic (QG) framework using the generalized stability theory. Optimal perturbations are obtained using a tangent linear QG model and its adjoint. Their fine-scale spatial structures are studied in details. Growth rates of optimal perturbations are shown to be extremely sensitive to the time interval of optimization: The most unstable perturbations are found for time intervals of about 3 days, while the growth rates continuously decrease towards the most unstable normal mode, which is reached after about 170 days. The horizontal structure of the optimal perturbations consists of an intense counter-shear spiralling. It is also extremely sensitive to time interval: for short time intervals, the optimal perturbations are made of a broad spectrum of high azimuthal wave numbers. As the time interval increases, only low azimuthal wave numbers are found. The vertical structures of optimal perturbations exhibit strong layering associated with high vertical wave numbers whatever the time interval. However, the latter parameter plays an important role in the width of the vertical spectrum of the perturbation: short time interval perturbations have a narrow vertical spectrum while long time interval perturbations show a broad range of vertical scales. Optimal perturbations were set as initial perturbations of the vortex lens in a fully non linear QG model. It appears that for short time intervals, the perturbations decay after an initial transient growth, while for longer time intervals, the optimal perturbation keeps on growing, quickly leading to a non-linear regime or exciting lower azimuthal modes, consistent with normal mode instability. Very long time intervals simply behave like the most unstable normal mode. The possible impact of optimal perturbations on layering is also discussed.

scholarly journals Radiomorphology of the Habib Sealer-Induced Resection Plane during Long-Time Followup:A Longitudinal Single Center Experience after 64 Radiofrequency-AssistedLiver Resections

HPB Surgery ◽  
2010 ◽  
Vol 2010 ◽  
pp. 1-7 ◽  
Author(s):  
Robert Kleinert ◽  
Roger Wahba ◽  
Christoph Bangard ◽  
Klaus Prenzel ◽  
Arnulf H. Hölscher ◽  
...  
Keyword(s):  
Liver Resection ◽  
Morphological Characteristics ◽  
Postoperative Mortality ◽  
Coagulation Necrosis ◽  
Time Interval ◽  
Safe Alternative ◽  
Time Points ◽  
Single Center Experience ◽  
Long Time

Background. Radiofrequency (RF-) assisted liver resection devices like the Habib sealer induce a necrotic resection plane from which a small margin of necrotic liver tissue remains in situ. The aim of the present paper was to report our long-time experience with the new resection method and the morphological characteristics of the remaining necrotic resection plane. Methods. 64 RF-assisted liver resections were performed using the Habib sealer. Followup was assessed at defined time points. Results. The postoperative mortality was 3,6% and morbidity was 18%. The followup revealed that the necrotic zone was detectable in all analyzed CT and MRI images as a hypodense structure without any contrast enhancement at all time points, irrespectively of the time interval between resection and examination. Conclusion. Liver resection utilizing radiofrequency-induced resection plane coagulation is a safe alternative to the established resection techniques. The residual zone of coagulation necrosis remains basically unchanged during a followup of three years. This has to be kept in mind when evaluating the follow up imaging of these patients.

LONG‐TIME RESPONSE PREDICTED BY EXACT ELASTIC RAY THEORY

Geophysics ◽  
1965 ◽  
Vol 30 (3) ◽  
pp. 363-368 ◽  
Author(s):  
T. W. Spencer
Keyword(s):  
Formal Solution ◽  
Intermediate Stage ◽  
Time Limit ◽  
Time Interval ◽  
Individual Response ◽  
Axially Symmetric ◽  
Long Time ◽  
The Difference ◽  
The Individual ◽  
Significant Figures

The formal solution for an axially symmetric radiation field in a multilayered, elastic system can be expanded in an infinite series. Each term in the series is associated with a particular raypath. It is shown that in the long‐time limit the individual response functions produced by a step input in particle velocity are given by polynomials in odd powers of the time. For rays which suffer m reflections, the degree of the polynomials is 2m+1. The total response is obtained by summing all rays which contribute in a specified time interval. When the rays are selected indiscriminately, the difference between the magnitude of the partial sum at an intermediate stage of computation and the magnitude of the correct total sum may be greater than the number of significant figures carried by the computer. A prescription is stated for arranging the rays into groups. Each group response function varies linearly in the long‐time limit and goes to zero when convolved with a physically realizable source function.

scholarly journals On Jensen-type Inequalities for Nonsmooth Radial Scattering Solutions of a Loglog Energy-Supercritical Schrödinger Equation

2018 ◽  
Vol 2020 (8) ◽  
pp. 2501-2541
Author(s):  
Tristan Roy
Keyword(s):  
Schrödinger Equation ◽  
Schrodinger Equation ◽  
A Priori ◽  
Time Interval ◽  
Type Estimate ◽  
A Priori Bound ◽  
Long Time ◽  
Supercritical Nonlinearity ◽  
Gamma S ◽  
Radial Scattering

Abstract We prove scattering of solutions of the loglog energy-supercritical Schrödinger equation $i \partial _{t} u + \triangle u = |u|^{\frac{4}{n-2}} u g(|u|)$ with $g(|u|) := \log ^{\gamma } {( \log{(10+|u|^{2})} )}$, $0 &lt; \gamma &lt; \gamma _{n}$, n ∈ {3, 4, 5}, and with radial data $u(0) := u_{0} \in \tilde{H}^{k}:= \dot{H}^{k} (\mathbb{R}^{n})\,\cap\,\dot{H}^{1} (\mathbb{R}^{n})$, where $\frac{n}{2} \geq k&gt; 1 \left(\text{resp.}\,\frac{4}{3}&gt; k &gt; 1\right)$ if n ∈ {3, 4} (resp. n = 5). The proof uses concentration techniques (see e.g., [ 2, 12]) to prove a long-time Strichartz-type estimate on an arbitrarily long time interval J depending on an a priori bound of some norms of the solution, combined with an induction on time of the Strichartz estimates in order to bound these norms a posteriori (see e.g., [ 8, 10]). We also revisit the scattering theory of solutions with radial data in $\tilde{H}^{k}$, $k&gt; \frac{n}{2}$, and n ∈ {3, 4}; more precisely, we prove scattering for a larger range of $\gamma$ s than in [ 10]. In order to control the barely supercritical nonlinearity for nonsmooth solutions, that is, solutions with data in $\tilde{H}^{k}$, $k \leq \frac{n}{2}$, we prove some Jensen-type inequalities.

scholarly journals Probability distributions of COVID-19 tweet posted trends use a nonhomogeneous Poisson process

2020 ◽  
Vol 1 (4) ◽  
pp. 229-238
Author(s):  
Devi Munandar ◽  
Sudradjat Supian ◽  
Subiyanto Subiyanto
Keyword(s):  
Social Media ◽  
Poisson Process ◽  
Exponential Distribution ◽  
Probability Distributions ◽  
Nonhomogeneous Poisson Process ◽  
Time Interval ◽  
Initial State ◽  
Time Intervals ◽  
Time Parameters ◽  
Parameter Values

The influence of social media in disseminating information, especially during the COVID-19 pandemic, can be observed with time interval, so that the probability of number of tweets discussed by netizens on social media can be observed. The nonhomogeneous Poisson process (NHPP) is a Poisson process dependent on time parameters and the exponential distribution having unequal parameter values and, independently of each other. The probability of no occurrence an event in the initial state is one and the probability of an event in initial state is zero. Using of non-homogeneous Poisson in this paper aims to predict and count the number of tweet posts with the keyword coronavirus, COVID-19 with set time intervals every day. Posting of tweets from one time each day to the next do not affect each other and the number of tweets is not the same. The dataset used in this study is crawling of COVID-19 tweets three times a day with duration of 20 minutes each crawled for 13 days or 39 time intervals. The result of this study obtained predictions and calculated for the probability of the number of tweets for the tendency of netizens to post on the situation of the COVID-19 pandemic.

scholarly journals IoT-based Running Time Monitoring System for Machine Preventive Maintenance Scheduling

ELKHA ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 33
Author(s):  
Erwin Sitompul ◽  
Agus Rohmat
Keyword(s):  
Monitoring System ◽  
Preventive Maintenance ◽  
Real Life ◽  
Remote Access ◽  
Time Interval ◽  
Monitoring And Control ◽  
Running Time ◽  
Damage And Failure ◽  
Simulation Purpose ◽  
And Control

Machines are valuable assets that need to be protected from damage and failure through proper maintenance measures. This paper proposes a system that automatically monitors the running time of machines and sends notifications regarding their preventive maintenance (PM) schedules. The system core consists of a programmable logic controller (PLC) and a human machine interface (HMI). The HMI is connected to an online platform via internet connection provided by a router, so that the monitoring result can be accessed via Android smartphone or laptop/PC. This IoT-based running time monitoring system (IRTMS) will be particularly helpful in implementation at an production site that consists of multiple various machines. The PM items of a machine may vary from cleaning, changing single component, to an overhaul, each with different time interval. By using the IRTMS, the user will have an overview of the PM schedules anytime and anywhere. The preparation of material, components, or tools can be known ahead of time. For simulation purpose, a prototype is constructed by using components as used in industrial real-life condition. Four output connections are provided to simulate the simultaneous monitoring of four machines. The IRTMS prototype is tested and completely successful on doing the running time monitoring, the running time reset, the PM notifications, and the remote access for monitoring and control.

scholarly journals ANALYSIS OF THE TIME‐DEPENDENT BEHAVIOUR OF COMPOSITE CROSS‐SECTIONS BY LAPLACE‐TRANSFORM

2005 ◽  
Vol 11 (3) ◽  
pp. 203-209
Author(s):  
Erich Raue ◽  
Thorsten Heidolf
Keyword(s):  
Laplace Transform ◽  
Cross Sections ◽  
Composite Structures ◽  
Time Dependent ◽  
Time Interval ◽  
Final State ◽  
Long Time ◽  
Time Dependent Behaviour ◽  
Linear Differential ◽  
Dependent Behaviour

Composite structures consisting of precast and cast in‐situ concrete elements are increasingly common. These combinations demand a mechanical model which takes into account the time‐dependent behaviour and analysis of the different ages of the connected concrete components. The effect of creep and shrinkage of the different concrete components can be of relevance for the state of serviceability, as well as for the final state. The long‐time behaviour of concrete can be described by the rate‐of‐creep method, combined with a discretisation of time. The internal forces are described for each time interval using a system of linear differential equations, which can be solved by Laplace‐transform.

scholarly journals Monitoring Robust Estimates for Compositional Data

2021 ◽  
Vol 50 (2) ◽  
pp. 16-37
Author(s):  
Valentin Todorov
Keyword(s):  
Compositional Data ◽  
Real Life ◽  
R Package ◽  
Diagnostic Tools ◽  
Data Set ◽  
Mahalanobis Distances ◽  
Robust Estimates ◽  
Real Life Data ◽  
Manufactured Exports ◽  
Parameter Values

In a number of recent articles Riani, Cerioli, Atkinson and others advocate the technique of monitoring robust estimates computed over a range of key parameter values. Through this approach the diagnostic tools of choice can be tuned in such a way that highly robust estimators which are as efficient as possible are obtained. This approach is applicable to various robust multivariate estimates like S- and MM-estimates, MVE and MCD as well as to the Forward Search in whichmonitoring is part of the robust method. Key tool for detection of multivariate outliers and for monitoring of robust estimates is the Mahalanobis distances and statistics related to these distances. However, the results obtained with thistool in case of compositional data might be unrealistic since compositional data contain relative rather than absolute information and need to be transformed to the usual Euclidean geometry before the standard statistical tools can be applied. Various data transformations of compositional data have been introduced in the literature and theoretical results on the equivalence of the additive, the centered, and the isometric logratio transformation in the context of outlier identification exist. To illustrate the problem of monitoring compositional data and to demonstrate the usefulness of monitoring in this case we start with a simple example and then analyze a real life data set presenting the technologicalstructure of manufactured exports. The analysis is conducted with the R package fsdaR, which makes the analytical and graphical tools provided in the MATLAB FSDA library available for R users.

scholarly journals CMF Signal Processing Method Based on Feedback Corrected ANF and Hilbert Transformation

2014 ◽  
Vol 14 (1) ◽  
pp. 41-47 ◽  
Author(s):  
Yaqing Tu ◽  
Huiyue Yang ◽  
Haitao Zhang ◽  
Xiangyu Liu
Keyword(s):  
Signal Processing ◽  
Phase Difference ◽  
Hilbert Transformation ◽  
Signal Frequency ◽  
Time Interval ◽  
Long Time ◽  
Novel Method ◽  
Adaptive Notch Filters ◽  
Difference Calculation ◽  
Value Decomposition

Abstract In this paper, we focus on CMF signal processing and aim to resolve the problems of precision sharp-decline occurrence when using adaptive notch filters (ANFs) for tracking the signal frequency for a long time and phase difference calculation depending on frequency by the sliding Goertzel algorithm (SGA) or the recursive DTFT algorithm with negative frequency contribution. A novel method is proposed based on feedback corrected ANF and Hilbert transformation. We design an index to evaluate whether the ANF loses the signal frequency or not, according to the correlation between the output and input signals. If the signal frequency is lost, the ANF parameters will be adjusted duly. At the same time, singular value decomposition (SVD) algorithm is introduced to reduce noise. And then, phase difference between the two signals is detected through trigonometry and Hilbert transformation. With the frequency and phase difference obtained, time interval of the two signals is calculated. Accordingly, the mass flow rate is derived. Simulation and experimental results show that the proposed method always preserves a constant high precision of frequency tracking and a better performance of phase difference measurement compared with the SGA or the recursive DTFT algorithm with negative frequency contribution

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