Time Dependence Of Parameters Research Articles

Real-Time Monitoring of Parameters and Diagnostics of the Technical Condition of Small Unmanned Aerial Vehicle’s (UAV) Units Based on Deep BiGRU-CNN Models

The paper describes an original technique for the real-time monitoring of parameters and technical diagnostics of small unmanned aerial vehicle (UAV) units using neural network models with the proposed CompactNeuroUAV architecture. As input data, the operation parameter values for a certain period preceding the current and actual control actions on the UAV actuators are used. A reference parameter set model is trained based on historical data. CompactNeuroUAV is a combined neural network consisting of convolutional layers to compact data and recurrent layers with gated recurrent units to encode the time dependence of parameters. Processing provides the expected parameter value and estimates the deviation of the actual value of the parameter or a set of parameters from the reference model. Faults that have led to the deviation threshold crossing are then classified. A smart classifier is used here to detect the failed UAV unit and the fault or pre-failure condition cause and type. The paper also provides the results of experimental validation of the proposed approach to diagnosing faults and pre-failure conditions of fixed-wing type UAVs for the ALFA dataset. Models have been built to detect conditions such as engine thrust loss, full left or right rudder fault, elevator fault in a horizontal position, loss of control over left, right, or both ailerons in a horizontal position, loss of control over the rudder and ailerons stuck in a horizontal position. The results of estimating the developed model accuracy on a test dataset are also provided.

Nonlinear Potential Scanning as a Novel Approach to Calculation of the Time Variable Galvanic Displacement Reaction Rate

AbstractA novel approach to estimate the rate of galvanic displacement reaction was proposed, which allowed the most accurate calculation of the displacement process rate at each moment of time by exact reproducing the open‐circuit conditions. We applied the method for mild steel samples immersed in pyrophosphate‐citrate electrolyte for Cu−Zn alloy electrodeposition. The time dependences of parameters of steel‐electrolyte interaction are obtained. The rate of steel dissolution in open circuit conditions increases by 1.6–2.9 times as compared with corrosion in pyrophosphate‐citrate medium. The results of our approach were verified by an independent experiment using anodic stripping of the obtained deposits.

Deep reinforcement learning for quantum gate control

How to implement multi-qubit gates efficiently with high precision is essential for realizing universal fault-tolerant computing. For a physical system with some external controllable parameters, it is a great challenge to control the time dependence of these parameters to achieve a target multi-qubit gate efficiently and precisely. Here we construct a dueling double deep Q-learning neural network (DDDQN) to find out the optimized time dependence of controllable parameters to implement two typical quantum gates: a single-qubit Hadamard gate and a two-qubit CNOT gate. Compared with traditional optimal control methods, this deep reinforcement learning method can realize efficient and precise gate control without requiring any gradient information during the learning process. This work attempts to pave the way to investigate more quantum control problems with deep reinforcement learning techniques.

О способе увеличения степени интеграции элементов в схеме приемного компаратора.

О способе увеличения степени интеграции элементов в схеме приемного компаратора.

Dynamics of plasma and ion flux in a vacuum neutron tube

Results of the numerical simulation of the formation of the ion beam in the accelerating gap of a vacuum neutron tube are presented. Calculations are performed with the KARAT code in a two-dimensional nonstationary formulation for plasma formed in arc discharge and inflowing into an accelerating gap with the given time dependences of parameters (density, expansion velocity). The small duration of the vacuum arc leads to a considerable change of parameters of inflowing plasma during the accelerating pulse. Two geometries are considered: the conventional and sectioned diode, in which the total voltage is divided between the anode, intermediate electrode, and cathode.

Extracting Business Cycles using Semi-Parametric Time-Varying Spectra with Applications to US Macroeconomic Time Series

A growing number of empirical studies provides evidence that dynamic properties of macroeconomic time series have been changing over time. Model-based procedures for the measurement of business cycles should therefore allow model parameters to adapt over time. In this paper the time dependencies of parameters are implied by a time dependent sample spectrum. Explicit model specifications for the parameters are therefore not required. Parameter estimation is carried out in the frequency domain by maximising the spectral likelihood function. The time dependent spectrum is specified as a semi-parametric smoothing spline ANOVA function that can be formulated in state space form. Since the resulting spectral likelihood function is time-varying, model parameter estimates become time-varying as well. This new and simple approach to business cycle extraction includes bootstrap procedures for the computation of confidence intervals and real-time procedures for the forecasting of the spectrum and the business cycle. We illustrate the methodology by presenting a complete business cycle analysis for two U.S. macroeconomic time series. The empirical results are promising and provide significant evidence for the great moderation of the U.S. business cycle.

Quantization of a 3D Nonstationary Harmonic plus an Inverse Harmonic Potential System

The Schrödinger solutions for a three-dimensional central potential system whose Hamiltonian is composed of a time-dependent harmonic plus an inverse harmonic potential are investigated. Because of the time-dependence of parameters, we cannot solve the Schrödinger solutions relying only on the conventional method of separation of variables. To overcome this difficulty, special mathematical methods, which are the invariant operator method, the unitary transformation method, and the Nikiforov-Uvarov method, are used when we derive solutions of the Schrödinger equation for the system. In particular, the Nikiforov-Uvarov method with an appropriate coordinate transformation enabled us to reduce the eigenvalue equation of the invariant operator, which is a second-order differential equation, to a hypergeometric-type equation that is convenient to treat. Through this procedure, we derived exact Schrödinger solutions (wave functions) of the system. It is confirmed that the wave functions are represented in terms of time-dependent radial functions, spherical harmonics, and general time-varying global phases. Such wave functions are useful for studying various quantum properties of the system. As an example, the uncertainty relations for position and momentum are derived by taking advantage of the wave functions.

The formation of an ion beam in a vacuum neutron tube

The formation of a deuteron beam in a diode with a plasma emitter that is integrated into the structure of a vacuum neutron tube is considered. Computations are carried out for plasma with given time dependences of parameters (density, relative concentration, and expansion velocity) at the inlet to an accelerating gap. It is shown that it is possible to increase the ion-beam current possible by sectioning the diode at the given external parameters.

Analyzing Density Operator in Thermal State for Complicated Time-Dependent Optical Systems

Density operator of oscillatory optical systems with time-dependent parameters is analyzed. In this case, a system is described by a time-dependent Hamiltonian. Invariant operator theory is introduced in order to describe time-varying behavior of the system. Due to the time dependence of parameters, the frequency of oscillation, so-called a modified frequency of the system, is somewhat different from the natural frequency. In general, density operator of a time-dependent optical system is represented in terms of the modified frequency. We showed how to determine density operator of complicated time-dependent optical systems in thermal state. Usually, density operator description of quantum states is more general than the one described in terms of the state vector.

Dielectric analysis of CMPS-supported ionic liquids (ILs) microspheres in model gasoline by means of dielectric relaxation spectroscopy

Real-time monitoring of dielectric behaviors of CMPS-supported imidazolium ionic liquids (ILs) microspheres in model gasoline was performed by dielectric relaxation spectroscopy (DRS) from 40Hz to 110MHz. One dielectric relaxation in MHz frequency range is obviously observed for all systems and determined to be closely related to the interfacial polarization. The interfacial polarization is attributed from the different conductivities between dispersed microspheres and model gasoline since imidazolium-based ionic liquids have been immobilized on the surfaces of dispersed microspheres in the form of optimized spatial configurations. Meanwhile, dielectric parameters (ɛl, κl, ɛh, κh and f0) for all the systems are obtained by fitting Cole–Cole equation to the dielectric data. From the dielectric parameters, Hanai equations are employed to calculate phase parameters (ϕ, κm, ɛp and κp), which is used to characterize the electrical and structural properties of constituent phases of suspensions of conducting particles in non-conducting medium. The time-dependences of dielectric parameters and phase parameters are investigated in detail, and interfacial electrokinetic model for suspension of dense particles has been employed for interpreting these time-dependences. Here, we found that possible π–complexation bond and π–π interaction between imidazole rings of ILs and thiophene are responsible for time-dependences of all parameters. Furthermore, the time-dependences of parameters indicate that the electron density (polarization strength) on surfaces of dispersed microspheres decreases with the increment of extraction time.

Time-variant assessment for adhesively bonded assemblies with non-linear behaviour in naval applications

Adhesive bonding is becoming a widely used assembling process in the naval field; it can allow great productivity, simplify design constraints and can lead, in general, to a significant weight reduction. Unfortunately, this technology is not completely mastered; parameters like the cure process, size of defects, joint adhesive thickness variations, size of parts to be assembled and non-linear behaviour of the adhesive joint, have to be considered to assess the risks and predict the service life. Moreover, for naval applications adapted state functions have to be proposed in order to take into account this variability of material properties, the time dependency of parameters like damage, solicitations or loads. Under these assumptions, time-independent reliability is insufficient to allow a pertinent-related failure probability calculation. The solution of such a problem can be given by the use of time-dependent reliability tools. This passes through coupling structural reliability software evaluation with a non-linear finite element code. This choice requires robust mechanical models able to describe the behaviour of naval structure with an acceptable numerical cost in order to perform the reliability study. This paper presents a time variant reliability approach based on the PHI2 method. Cohesive-zone models are used to model the adhesive. This choice allows limiting the numerical cost of simulations and permits us to model the non-linear behaviour of adhesive. It also presents a good compromise between numerical costs and quality of results. The damage at the interface can be modelled and it has been proven that using cohesive zone models is well suited for bonded joints as the possible degradation zone is well defined. In order to determine the cohesive zone model parameters, tests were performed. The most relevant results are presented. Different numerical results showing the feasibility of this approach for adhesively bonded assemblies are discussed and the case of a representative part of a naval structure has been studied in this paper.

Temporal Variability and Social Heterogeneity in Disease Transmission: The Case of SARS in Hong Kong

The extent to which self-adopted or intervention-related changes in behaviors affect the course of epidemics remains a key issue for outbreak control. This study attempted to quantify the effect of such changes on the risk of infection in different settings, i.e., the community and hospitals. The 2002–2003 severe acute respiratory syndrome (SARS) outbreak in Hong Kong, where 27% of cases were healthcare workers, was used as an example. A stochastic compartmental SEIR (susceptible-exposed-infectious-removed) model was used: the population was split into healthcare workers, hospitalized people and general population. Super spreading events (SSEs) were taken into account in the model. The temporal evolutions of the daily effective contact rates in the community and hospitals were modeled with smooth functions. Data augmentation techniques and Markov chain Monte Carlo (MCMC) methods were applied to estimate SARS epidemiological parameters. In particular, estimates of daily reproduction numbers were provided for each subpopulation. The average duration of the SARS infectious period was estimated to be 9.3 days (±0.3 days). The model was able to disentangle the impact of the two SSEs from background transmission rates. The effective contact rates, which were estimated on a daily basis, decreased with time, reaching zero inside hospitals. This observation suggests that public health measures and possible changes in individual behaviors effectively reduced transmission, especially in hospitals. The temporal patterns of reproduction numbers were similar for healthcare workers and the general population, indicating that on average, an infectious healthcare worker did not infect more people than any other infectious person. We provide a general method to estimate time dependence of parameters in structured epidemic models, which enables investigation of the impact of control measures and behavioral changes in different settings.

Testing for parameter stability: the Spanish consumption function

This study tests for parameter instability in the Spanish consumption function. To that end, a new test for time dependence of parameters is used and compared with other relevant tests. As opposed to other tests this new one is concerned with detecting parameter variation in frequency domain.

Theory and computation of the reference dependence and residual service life of a machine

The diagnostic parameter—time dependence, usually used for prediction of the residual service time, is given here its theoretical grounding. The relationships involved are derived on the basis of the machine's heat balance for two time approaches—short-term (starting time) and—long-term (service time). The diagnostic parameter considered is the temperature change rate during the running-in period of the machine. The reference dependence obtained from theoretical values of the diagnostic parameter is compared against its counterpart by the traditional empirical method. The residual service life calculated by these two approaches is also analyzed. It is shown that the theoretical consideration is valid and can be applied in reliable machine diagnostics.

A Note to the Variable Sorptivity Infiltration Equation

A simplification for the variable sorptivity infiltration equation of Poulovassilis et al. (1989) is proposed. The resulting equation has three parameters Sx, c and K0. From these, Sx and c are considered as fitting parameters and K0 as a physical one. The new empirical infiltration equation is tested for precision, parameter time-dependence and applicability for soil surveys. The test was carried out by comparison with reference solutions i.e. infiltration data obtainedexperimentally, analytically or numerically for two different head conditionsat the infiltration surface. A good agreement is observed for all examinedcases. The dependence of the fitting parameters Sx and c on the initialand boundary conditions, as well as the error that arises by taking intoaccount different values of them, are examined. In fine textured soilsparameter c seems to be very small, so that one can easily suppose that the proposed equation reduces to the well-known Philip's infiltration equation (Philip, 1957).

Unit roots versus other types of time heterogeneity, parameter time dependence and superexogeneity

AbstractThis paper stresses the restrictive nature of the standard unit root/cointegration assumptions and examines a more general type of time heterogeneity, which might characterize a number of economic variables, and which results in parameter time dependence and misleading statistical inference. We show that in such cases ‘operational’ models cannot be obtained, and the estimation of time‐varying parameter models becomes necessary. For instance, economic processes subject to endemic change can only be adequately modelled in a state space form. This is a very important point, because unstable models will break down when used for forecasting purposes. We also discuss a new test for the null of cointegration developed by Quintos and Phillips (1993), which is based on parameter constancy in cointegrating regressions. Finally, we point out that, if it is possible to condition on a subset of superexogenous variables, parameter instability can be handled by estimating a restricted system. Copyright © 2002 John Wiley & Sons, Ltd.

Time Dependence of the Reaction-Diffusion Simulation of the Postexposure Bake Process of Deep-Ultraviolet Resists

The time-dependent postexposure bake (TDPEB) simulator, previously reported to include the time dependence of parameters in the entire course of the postexposure bake (PEB) simulation, is used to simulate the PEB process with different combinations of bake times and pattern dimensions. Comparison of the results of simulation shows that the time dependence of the simulation is greater for shorter bake times.

Quality control of gamma-ray spectrometry measurements

Specific techniques have been implemented to assess the quality of routine gamma-ray measurements and the associated analysis procedures. Appropriate steps monitor three factors influencing the quality of performance: the performance of the spectrometer, the quality of the measurement and the quality of the peak analysis. In order to illustrate the approach, time dependencies of parameters describing the performance of the spectrometer, the quality of the measurements and the sample activities are presented.

Gaussian parametric failure-rate model with application to quartz-crystal device aging

A model for predicting parametric failure rate for a time-dependent normal (Gaussian) distribution is obtained in closed form. The model can be applied to any device parameter that can be modeled by a normal distribution when the parameter time-dependence is known. The model is applied to the aging law of quartz surface-acoustic-wave (SAW) devices. The parametric failure rate of a 295.6 MHz SAW filter was obtained at 75 degrees C based on data for 80 SAW filters. The frequency and phase parameters of the population were characterized over time using an accelerated test. The example illustrates how the mean and standard deviation can be characterized over time for the parametric distribution. Then using these results for the representative lot, the model predicts the population's parametric failure rate at use conditions. This application shows that when a characteristic parameter for a population device being investigated is normally distributed and ages in log(time), then the failure rate has a lognormal form in time, and that a sample standard deviation for time-dependent parameters is also time dependent.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

INFILTRATION UNDER PONDED CONDITIONS

We analyzed six different infiltration equations—those of Kostiakov (1932), Horton (1940), Mezencev (1948), Green and Ampt (1911), Philip (19576) and Par-lange et al. (1985)—for precision, parameter time-dependence, and applicability for predictive use. The tests were carried out by comparison with reference solutions, i.e., analytical, experimental, or numerical for two different head conditions at the soil surface. The results show that all the infiltration equations but those of Kostiakov and Horton, satisfy sufficiently well the imposed precision criterion. Only one model, however, the Parlange infiltration equation, has the advantage of using parameters that are constant in time and independent of the number of data points chosen for their evaluation procedure. The parameters entering into the other algebraic infiltration equations have to be considered as fitting parameters without physical significance and representative only of the experiment for which they are determined.