Function Of Delay Research Articles

Quasi-maximum likelihood-based estimator of the hyperbolic frequency modulated signals

The quasi-maximum likelihood (QML) algorithm has been extended to estimate the phase parameters and the instantaneous frequency (IF) of the hyperbolic frequency modulated (HFM) signals. The Nelder-Mead simplex algorithm (NMSA) is adopted for a fine estimation. The obtained accuracy is excellent with the estimates achieving the Cramer-Rao lower bound (CRLB) above the signal-to-noise (SNR) threshold of 0 dB. The proposed technique is capable of functioning with signals that are sampled below the requirements of the sampling theorem, which is particularly important for HFM signals. Additionally, there are no limitations for signals with monotonic IF and/or group delay (GD) functions.

Resolving Nonlinear Recombination Dynamics in Semiconductors via Ultrafast Excitation Correlation Spectroscopy: Photoluminescence versus Photocurrent Detection.

We explore the application of excitation correlation spectroscopy to detect nonlinear photophysical dynamics in two distinct semiconductor classes through time-integrated photoluminescence and photocurrent measurements. In this experiment, two variably delayed femtosecond pulses excite the semiconductor, and the time-integrated photoluminescence or photocurrent component arising from the nonlinear dynamics of the populations induced by each pulse is measured as a function of inter-pulse delay by phase-sensitive detection with a lock-in amplifier. We focus on two limiting materials systems with contrasting optical properties: a prototypical lead-halide perovskite (LHP) solar cell, in which primary photoexcitations are charge photocarriers, and a single-component organic-semiconductor diode, which features Frenkel excitons as primary photoexcitations. The photoexcitation dynamics perceived by the two detection schemes in these contrasting systems are distinct. Nonlinear-dynamic contributions in the photoluminescence detection scheme arise from contributions to radiative recombination in both materials systems, while photocurrent arises directly in the LHP but indirectly following exciton dissociation in the organic system. Consequently, the basic photophysics of the two systems are reflected differently when comparing measurements with the two detection schemes. Our results indicate that photoluminescence detection in the LHP system provides valuable information about trap-assisted and Auger recombination processes, but that these processes are convoluted in a nontrivial way in the photocurrent response and are therefore difficult to differentiate. In contrast, the organic-semiconductor system exhibits more directly correlated responses in the nonlinear photoluminescence and photocurrent measurements, as charge carriers are secondary excitations only generated through exciton dissociation processes. We propose that bimolecular annihilation pathways mainly contribute to the generation of charge carriers in single-component organic semiconductor devices. Overall, our work highlights the utility of excitation correlation spectroscopy in modern semiconductor materials research, particularly in the analysis of nonlinear photophysical processes, which are deterministic for their electronic and optical properties.

Consensus for Hegselmann–Krause type models with time variable time delays

In this paper, we analyze a Hegselmann–Krause opinion formation model with time variable time delay and prove that if the influence function is always positive, then there is exponential convergence to consensus without requiring any smallness assumptions on the time delay function. The analysis is then extended to a model with distributed time delay.

A new approach to estimating link performance on Indonesian urban roads: deriving the BPR 1964 function

Predictions of traffic volumes on road networks must be precise for transportation planning, and equilibrium trip assignment models based on the Volume Delay Function (VDF) are typically employed. In 1964, the U.S. Bureau of Public Roads (BPR) created a VDF widely used in many countries, including Indonesia. However, using capacity manuals from Western nations in Indonesia did not produce the desired results due to differences in traffic composition and driver behaviour. Using the Indonesian Highway Capacity Manual’s macroscopic fundamental diagram, this paper aims to derive a more accurate VDF for Indonesia. This method enables the development of a VDF tailored to the unique traffic conditions in Indonesia. It can enhance the precision of traffic volume forecasts in the region. The BPR function parameters tends to overestimate travel time delay, making the road network model flow misestimated. This is presumably caused by traffic count survey inability to record the build-up of traffic flow in the urban network during peak traffic periods.

Balancing Security and Energy-Efficiency in Vehicular Ad-Hoc Sensor Networks Using EHDSORP

Automobile networks have been the focus of growing amounts of research from scholarly community and organization as a method to improve traffic safety and provide drivers and passengers with real-time data. Beyond that, however, what is driving the expansion of VANETs is the need for a safe and secure network in moving vehicles. Ad hoc vehicular networks are made up of intelligent, on-the-road cars that can exchange data with one other and with permanent roadside infrastructure. In order to provide an energy-efficient and secure routing for ad-hoc sensor networks, a balancing security-based energy-aware routing leveraging the hybrid Fuzzy logic technique with dove swarm optimization-based routing (HFLDSOR) protocol is proposed in this study. The sensor nodes in this balancing security-based energy-aware routing are first set up in the ad hoc network. The clustering is carried out using an estimate of the distance between each node, and the cluster head (CH) is chosen using a fuzzy logic method. After the selection of the CH, the distance between each node, the quantity of energy left, and the number of neighbours for each node are evaluated as fuzzy logic criterion. In order to choose the best routing route for secured communication, the trustworthy nodes are forwarded. Balancing security-based hybrid vehicles that use less energy The optimum paths to the target are chosen using fuzzy logic method with dove swarm optimization-based routing (SE- HFLDSOR) protocol approach based on the parameters such as distance delay and energy objective function. Consequently, the SE- HFLDSOR protocol was used for safe and energy-efficient routing. The suggested model outperforms the comparable current procedures, according to the assessment performed using the MATLAB simulation tool. Hence, the SE- HFLDSOR protocol was appropriate for real-time applications.

Fractional and MDD analysis of piezo-photo-thermo-elastic waves in semiconductor medium

This manuscript examines the effects of memory-dependent and fractional-order derivatives on a novel generalized piezo-thermo-elastic semiconductor model. The medium is homogenous and orthotropic, subjected to photo-thermal excitation. The governing equations include fractional-order parameters, relaxation time, time delay, and kernel function tailored to specific problem requirements. Normal mode method use to solve the equations, yielding analytical expressions. Graphical representations show physical field distribution across various fractional-order parameters, kernel functions, time delay, and frequency values. This study has the potential to advance precise model development and future simulations.

Isogeny computation on Kummer lines and applications

Isogeny-based cryptography has been the hotspot in recent years owing to its resistance to quantum computing attacks. Unfortunately, efficiency is the main bottleneck that limits its cryptographic applications. Inspired by the efficient implementations of Kummer lines, we formalize the isogenies on Kummer lines. In particular, we derive the explicit formulae of distinct 2-isogenies, consisting of several transforms between different Kummer lines, followed by some appealing isomorphic properties. As an additional contribution, we establish the formulae of odd-degree isogenies and show that 3-isogenies can be decomposed into three similar operations. Furthermore, with appropriate optimizations, we present the algorithms of computing the 2-isogenies over Fp with the ability to obtain the images simultaneously. For the setup of Verifiable Delay Functions and Delay Encryptions, our method reduces the number of operations with the potential of more compact schemes.

Conditions of stability and guaranteed convergence rate for linear time-varying discrete-time delay systems

This work introduces novel results on the stability of linear time-varying discrete-time delay systems, addressing both internal stability and input-to-state stability. We start from the special case of positive delay systems and provide conditions of global exponential stability, both delay-dependent and delay-independent. Moreover, we formulate an explicit bound on the exponential decay rate of the state evolution, as a function of the maximum delay. We then show that the aforementioned stability conditions also prove input-to-state stability. The stability conditions consist of simple linear inequalities, albeit infinite-many due to the time-varying nature of the system. To overcome the computational burden, we also introduce a simple relaxation that allows to check the stability with a finite test, at the expense of conservatism. Finally, leveraging comparison systems and results from the theory of non-negative matrices, we generalize all the aforementioned results to systems with no sign constraint, for which we still provide stability conditions by means of linear inequalities and guaranteed convergence rate. Some consequences and a comparative example are provided for the well investigated special case of systems with constant matrices and time-varying delays.

Robust Gas-Path Fault Diagnosis with Sliding Mode Applied in Aero-Engine Distributed Control System

The technology of aero-engine gas-path fault diagnosis is an important way to improve flight safety and reliability and reduce maintenance costs. With the maturity of the new-generation engine distributed control system (DCS), uncertainties such as bus packet loss, time delay, and node function degradation have increasingly highlighted new challenges to engine fault diagnosis. At present, linear Kalman filter (LKF) is widely researched and used in engine fault detection and isolation (FDI), but its robustness has proved to be not strong. However, the sliding mode observer (SMO) is not only capable of fault reconstruction but also robust to system uncertainties and disturbances due to its unique discontinuous switching term, which tends to be an effective way to achieve robust fault diagnosis for aero engines and DCS with many uncertainties. This paper initially develops a distributed bus packaging model that supports time-delay and packet-loss simulating and timing planning based on SimEvents, providing a basis for the model-based design and verification. Then the SMO is adopted to design a robust gas-path diagnosis method for engine DCS, and the robust observing accuracy is improved by combining high-order sliding mode theory, LMI optimized observation matrix, and variable gain. The simulation results show the effectiveness and advantages in engine DCS application scenarios.

Forecasting clean energy power generation in China based on a novel fractional discrete grey model with a dynamic time-delay function

Clean energy plays an essential role in responding to environmental crises. Accurate forecasting of clean energy power generation can provide necessary references for the formulation of energy policy. This paper proposes a novel fractional discrete grey model with a dynamic time delay function (DTDFF-DGM (1,1)) to forecast clean energy power generation. This model introduces the fractional accumulation operator and the dynamic time-delay function into the discrete grey model, which ensures the priority of new information in the original data and improves the model's adaptability to different sample data. The optimal parameters of the model are calculated by the dynamic linkage between the fitting error and the test error, which effectively avoids the overfitting problem. Empirical studies have proved that the model has better prediction accuracy compared to other methods. Finally, the proposed model is employed to forecast clean energy power generation in China. The results show that from 2020 to 2025, the overall growth rate of hydropower, wind power and nuclear power in China will be 9.27%, 119.61% and 36.38%, respectively. Based on the discussion of the forecast results, relevant policy suggestions were made. This paper realizes the transformation from a static model to a dynamic model in methodology and promotes the sustainable development of clean energy power generation in application.

Delay-Controlled Bidirectional Traffic Setup Scheme to Enhance the Network Coding Opportunity in Real-Time Industrial IoT Networks

Recently, network coding has become a promising transmission approach to support high throughput and low latency in distributed multi-hop networks. In this paper, we develop a delay-controlled distributed route establishment scheme that can provide maximal bidirectional transmission to enhance network coding gain while satisfying a time-critical route setup. The scheme is called network coding-aware delayed store and forwarding (NC-DSF). It delays the received route information packets before forwarding them according to the link status and network topology. We propose a tight delay function derived using a strict end-to-end delay bound for delay control. Subsequently, we suggest a relaxed delay function derived using realistic and practical conditions. Finally, we propose a load-weighted delay function considering the trade-off between bidirectionality and network-load balancing. The simulations confirm that the proposed scheme offers increased throughput and decreased latency in mesh and random multi-hop networks. The proposed transmission scheme, NC-DSF, can be efficiently employed in future industrial internet of things networks requiring a time-constrained route setup, high throughput, and low latency.

Estimating Demand Volume for Signalized Corridors Under Oversaturated Conditions Using Aggregated Probe Vehicle Speed Data

Measuring demand directly with vehicle sensors is not possible when demand is larger than capacity for an extended period, as the queue grows beyond the sensor, and the flow measurements at a given point cannot exceed the capacity of the section. The main objective of this study is to develop methods that could be implemented in practice based on readily available data. To this end, two methods are proposed: an innovative method based on shockwave theory and the volume delay function adapted from the Highway Capacity Manual (7th edition). Both methods primarily rely on probe vehicle speeds (e.g., from INRIX) as the input data and the capacity of the segment or bottleneck being analyzed. Probe vehicle data are used to determine the critical times when the queue reaches the end or beginning of a road segment. From these critical times, the shockwave speed for the boundary between congested (high density) traffic and arriving (low density) traffic is estimated. The proposed methods are tested with simulation data generated in VISSIM and validated based on volume data from the field. The field data are collected from a congested arterial in Virginia Beach, VA, and include the ground truth volumes and INRIX speed data aggregated at one-minute intervals. The results show that both methods are effective for estimating the demand volume and produce less than 4% error when tested with field data.

Effects of short-term nicotine deprivation on delay discounting among young, experienced, exclusive ENDS users: An initial study.

Delay discounting describes how rapidly delayed rewards lose value as a function of delay and serves as one measure of impulsive decision-making. Nicotine deprivation among combustible cigarette smokers can increase delay discounting. We aimed to explore changes in discounting following nicotine deprivation among electronic nicotine delivery systems (ENDS) users. Thirty young adults (aged 18-24 years) that exclusively used ENDS participated in two laboratory sessions: one with vaping as usual and another after 16 hr of nicotine deprivation (biochemically assessed). At each session, participants completed a craving measure and three hypothetical delay discounting tasks presenting choices between small, immediate rewards and large, delayed ones (money-money; e-liquid-e-liquid; e-liquid-money). Craving for ENDS significantly increased during short-term nicotine deprivation relative to normal vaping. Delay discounting rates in the e-liquid now versus money later task increased (indicating a shift in preference for smaller, immediate rewards) following short-term nicotine deprivation relative to vaping as usual, but no changes were observed in the other two discounting tasks. Short-term nicotine deprivation increased the preference for smaller amounts of e-liquid delivered immediately over larger, monetary awards available after a delay in this first study of its kind. As similar preference shifts for drug now versus money later have been shown to be indicative of increased desire to use drug as well as relapse risk, the findings support the utility of the current model as a platform to explore interventions that can mitigate these preference shifts. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Reinforcement Learning-Based Optimization Framework for Application Component Migration in NFV Cloud-Fog Environments

By decoupling network functions from the underlying hardware, Network Function Virtualization (NFV) allows application components to be implemented as sets of Virtual Network Functions (VNFs) chained in a specific order, represented by VNF-Forwarding Graphs (VNF-FG). Fog computing is instrumental to tap into the full potential of NFV by deploying VNFs in close proximity to end-users, thus decreasing the latency significantly. However, the mobility of end-users and the fog nodes, and the limited fog nodes coverage results in service discontinuity and may increase application delay. Application component migration offers great potential to address this issue. In this paper, we propose a component migration strategy in an NFV-based hybrid cloud/fog system considering the mobility of both end-users and fog nodes. We use the Gauss-Markov mobility model and a random walk mobility model for fog nodes and end-user devices, respectively. We modeled the problem mathematically, which minimizes the aggregated weighted function of application delay and cost. However, considering the mobility of both end-users and fog nodes makes the problem quite complex. Hence, we propose a Deep Reinforcement Learning (DRL) approach to decide where and when to migrate application components and to achieve rapid decision-making. Simulation results demonstrate that the proposed scheme performs well. It offers favorable convergence and outperforms existing algorithms in terms of application delay and migration costs.

A mid-infrared laser microscope for the time-resolved study of light-induced protein conformational changes.

We have developed a confocal laser microscope operating in the mid-infrared range for the study of light-sensitive proteins, such as rhodopsins. The microscope features a co-aligned infrared and visible illumination path for the selective excitation and probing of proteins located in the IR focus only. An external-cavity tunable quantum cascade laser provides a wavelength tuning range (5.80-6.35 µm or 1570-1724cm-1) suitable for studying protein conformational changes as a function of time delay after visible light excitation with a pulsed LED. Using cryogen-free detectors, the relative changes in the infrared absorption of rhodopsin thin films around 10-4 have been observed with a time resolution down to 30ms. The measured full-width at half maximum of the Airy disk at λ = 6.08 µm in transmission mode with a confocal arrangement of apertures is 6.6 µm or 1.1λ. Dark-adapted sample replacement at the beginning of each photocycle is then enabled by exchanging the illuminated thin-film location with the microscope mapping stage synchronized to data acquisition and LED excitation and by averaging hundreds of time traces acquired in different nearby locations within a homogeneous film area. We demonstrate that this instrument provides crucial advantages for time-resolved IR studies of rhodopsin thin films with a slow photocycle. Time-resolved studies of inhomogeneous samples may also be possible with the presented instrument.

An analytical frequency response function for fluidelastic instability model of a normal triangular array in cross-flow

A new model based on Theodorsen’s classical theory of aerodynamic instability and the mechanism of flutter is proposed to explain the origin of the time delay, an important parameter for fluidelastic instability prediction, between the tube motion and the non-linear fluidelastic forces. Using this model, a novel time delay function has been theoretically derived with no reliance on unsteady fluid force data, as was the case with earlier models. A stability analysis is carried out based on the new time delay function combined with the experimental static fluid forces for a range of mass damping parameters. The predicted stability threshold is found to compare well with experimental stability data.

Using convolutional neural networks to detect GNSS multipath.

Global Navigation Satellite System (GNSS) multipath has always been extensively researched as it is one of the hardest error sources to predict and model. External sensors are often used to remove or detect it, which transforms the process into a cumbersome data set-up. Thus, we decided to only use GNSS correlator outputs to detect a large-amplitude multipath, on Galileo E1-B and GPS L1 C/A, using a convolutional neural network (CNN). This network was trained using 101 correlator outputs being used as a theoretical classifier. To take advantage of the strengths of convolutional neural networks for image detection, images representing the correlator output values as a function of delay and time were generated. The presented model has an F score of 94.7% on Galileo E1-B and 91.6% on GPS L1 C/A. To reduce the computational load, the number of correlator outputs and correlator sampling frequency was then decreased by a factor of 4, and the convolutional neural network still has an F score of 91.8% on Galileo E1-B and 90.5% on GPS L1 C/A.

Ultrafast quantum path interferometry to determine the electronic decoherence time of the electron-phonon coupled system in n -type gallium arsenide

Quantum coherence is the key to new quantum technologies, although the details of decoherence processes and times are still not well understood in solids. We demonstrate how to measure the decoherence time of electronic excited states in $n$-type gallium arsenide ($n$-GaAs) crystals using a relative-phase locked double pulse excitation method and quantitatively evaluate with a simple model including temperature dependence. The interference patterns of both electronic and phonon coherence are observed in $n$-GaAs using ultrafast quantum path interferometry with $\ensuremath{\pi}/4$ polarized femtosecond pulses, via the amplitude of longitudinal optical phonons as a function of pump-pump delay. The electronic coherence shows uplifting and splitting in the collapse and revival of the electronic interference, which is sensitive to temperature, and these features are well reproduced using a simple quantum mechanical model. The decoherence time is determined using quantum calculations, from the splitting and uplifting in the interference shape, to be $27.8\ifmmode\pm\else\textpm\fi{}0.5, 23.0\ifmmode\pm\else\textpm\fi{}0.3$, and $12.9\ifmmode\pm\else\textpm\fi{}0.3$ fs at 10, 90, and 290 K, respectively. The temperature dependence of the decoherence time is well reproduced by the density of electrons in the conduction band with the group velocity of the photoinduced electrons.

Results on existence of solutions in nonlocal partial functional integrodifferential equations with finite delay in nondense domain

In this work, to show the existence and uniqueness solution of functional integrodifferential equation with nonlocal condition and finite delay function. This article contains continuously dependence of integral solution and existence of strict solution established by using integrated resolvent operator theory with support of Lipschitz continuous. In this article the operator (T(t))t⩾0 is assumed the locally Lipschitz continuous integrated resolvent operator and proved the existence of strict solution on reflexive and general Banach spaces. Finally an example is given related to this work.

Delay Discounting for HIV/STI Testing.

Wait time in healthcare is an important barrier to HIV/STI testing. Using a delay discounting approach, the current study examined a systematic reduction in testing likelihood as a function of delay (wait time) until testing. In Study 1 (N = 421; data collected in 2019), participants were randomly assigned to either a chlamydia/gonorrhea group or HIV group. A delay discounting task asked them to report how likely they would get tested for the assigned STI if they had to wait for the test (the delay durations varied within persons). In Study 2 (N = 392; data collected in 2020), we added a smaller, sooner outcome (consultation without testing) and tested whether the effect of delay was mediated by perceived severity of the STIs. In both studies, the subjective value of a delayed STI test was discounted. That is, people were less likely to undergo STI testing as the delay to STI testing increased. The chlamydia/gonorrhea group discounted delayed testing more than the HIV group (i.e., the effect of delay on testing decisions was stronger for the former). This effect was statistically mediated by perceived severity. We found evidence for delay discounting for HIV/STI testing and that testing decisions were more susceptible to delay when the test was for relatively mild STIs. Even mild STIs can cause serious health damage if left untreated. The findings provide strong argument for policies aimed to reduce wait times in healthcare, especially for relatively mild STIs.