Showing papers on "Impulse (physics) published in 2022"
TL;DR: In this paper , the authors report the construction of synchronization criteria for the delayed impulsive epidemic models with reaction-diffusion under the Neumann boundary value, and their effectiveness is illustrated by numerical examples.
Abstract: This paper reports the construction of synchronization criteria for the delayed impulsive epidemic models with reaction–diffusion under the Neumann boundary value. Different from the previous literature, the reaction–diffusion epidemic model with a delayed impulse brings mathematical difficulties to this paper. In fact, due to the existence of second-order partial derivatives in the reaction–diffusion model with a delayed impulse, the methods of first-order ordinary differential equations from the previous literature cannot be effectively applied in this paper. However, with the help of the variational method and an appropriate boundedness assumption, a new synchronization criterion is derived, and its effectiveness is illustrated by numerical examples.
37 citations
TL;DR: In this article , a novel impulsive event-triggered mechanism (IETM) which can exclude the Zeno behavior for nonlinear impulsive systems is designed, and sufficient conditions which establish the relationship between impulse strength and IETM for input-to-state stability (ISS) are proposed.
Abstract: This article investigates input-to-state stability (ISS) of nonlinear systems via event-triggered impulsive control method. A novel impulsive event-triggered mechanism (IETM) which can exclude the Zeno behavior for nonlinear impulsive systems is designed. Some sufficient conditions which establish the relationship between impulse strength and IETM for ISS property are proposed. It is shown that under the designed IETM, a flexible impulsive control strategy can be provided. Since impulses only occur when the event which is related to the states of the system is triggered, the burden of the transmission of information can be reduced dramatically. Examples are presented to show the effectiveness of our proposed results.
35 citations
TL;DR: In this paper , the authors investigated the interrelationships between e-impulse buying tendencies (e-IBT) and customer satisfaction empirically, and the customers' intent to continue e-shopping is also investigated.
Abstract: The global COVID-19 outbreak and consequent lockdown pushed consumers to engage in more e-shopping, which could lead to e-impulse purchases (e-IB). The purpose of this study is to investigate the interrelationships between e-impulse buying tendencies (e-IBT), e-impulse buying (e-IB), and customer satisfaction empirically (CS). The customers' intent to continue e-shopping is also investigated. Data was collected from 580 consumers in India's Union Territory of Delhi using a standardized instrument. The psychometric features of the research survey instrument were first verified using the LISREL Structural Equation Modeling Package. Hayes (2018) PROCESS was used to evaluate the moderated mediation model and hypotheses. The association between e-IBT and CS was empirically demonstrated to be mediated by e-IB. Furthermore, e-IBT is associated to e-IB in a good way. Furthermore, e-IB is positively connected to CS, indicating that consumers intend to continue shopping online. The findings also show that the e-IBT interacts with the website (first moderator) and stimulants and promotions (second moderator) to significantly influence the e-IB. Further, hedonic motives modify the e-IB-CS relationship.
30 citations
TL;DR: Experimental results indicate that APMESR can effectively extract incipient bearing fault features and outperforms other well-advanced methods.
26 citations
TL;DR: In this article , two neural networks via self-organizing learning can find their optimal architectures corresponding to finite impulse response (FIR) filter and recursive observer for FD purposes for dynamic systems.
Abstract: With the aid of neural networks, this article develops two data-driven designs of fault detection (FD) for dynamic systems. The first neural network is constructed for generating residual signals in the so-called finite impulse response (FIR) filter-based form, and the second one is designed for recursively generating residual signals. By theoretical analysis, we show that two proposed neural networks via self-organizing learning can find their optimal architectures, respectively, corresponding to FIR filter and recursive observer for FD purposes. Additional contributions of this study lie in that we establish bridges that link model- and neural-network-based methods for detecting faults in dynamic systems. An experiment on a three-tank system is adopted to illustrate the effectiveness of two proposed neural network-aided FD algorithms.
25 citations
TL;DR: In this article , the results of modeling a new nonlinear multi-stable QZEH (quasi-zero energy harvester) system for harvesting energy from vibrating mechanical devices are presented.
24 citations
TL;DR: A wave-to-wire analytical code modeling an entire wave energy converter based on the oscillating water column (OWC) technology, operating with either a Wells or an impulse turbine, was developed in this article.
22 citations
TL;DR: A novel intelligent rolling bearing fault severity recognition method that can better recognize the fault severities of rolling bearings than the comparison methods is proposed.
Abstract: Rolling bearing vibration signals exhibit typically complex modulation characteristics, and usually present nonstationary features. The defect of a rolling bearing is mainly manifested by impulses carried by resonance vibration, and the resonance frequency is independent of the operation conditions. Recent studies have correlated the characteristics of impulses with the fault severity of rolling bearings. However, the impulses are extracted manually, and the fault severity is evaluated by manually analyzing the target impulses or the matched atoms. This paper takes advantage of impulses, and proposes a novel intelligent rolling bearing fault severity recognition method. The method includes two modules, i.e., impulse mining and fault recognition. Recently, matrix profile (MP) has emerged as a promising method of mining the motifs in a time-domain signal. In the first module, MP is firstly introduced to the field of fault diagnosis, and it is conducted to mine the impulses from vibration signals. In the second module, convolutional neural network (CNN) combined with softmax regression is applied to automatically extract the discriminatory features from the mined impulses and accomplish the fault severity recognition. The proposed method is evaluated by the lab experimental bearing signals, and further validated by the signals collected from a wind turbine simulator with faulty high-speed shaft roller bearing. The results demonstrate that the proposed method can better recognize the fault severities of rolling bearings than the comparison methods.
22 citations
TL;DR: In this article , an adaptive period matching enhanced sparse representation (APMESR) algorithm is developed to address the issue of bearing incipient fault feature extraction, which can effectively extract incipient bearing fault features and outperforms other well-advanced methods.
21 citations
01 Jan 2022
TL;DR: A highly efficient & machine learning based TinyML model is designed for determining the resonance of Cough on instantaneous basis and has been found to achieve almost 97% accuracy of recognition.
Abstract: In this research paper, a system for the detection of cough is made with Edge Impulse Studio and Arduino 33 BLE Sense. It is able to distinguish between actual cough and a general undesired signal in the background. Edge Impulse Studio has been utilized in this article for training a large dataset of the various samples for cough as well as undesired noise. A highly efficient & machine learning based TinyML model is designed for determining the resonance of Cough on instantaneous basis. The proposed system has been found to achieve almost 97% accuracy of recognition.
21 citations
TL;DR: In this paper , the high boiling point and poor solubility of green solvents lead to the high cost of green solvent-treated organic solar cells (OSCs) for printing large-area photovoltaic devices.
Abstract: Green solvent-treated organic solar cells (OSCs) have demonstrated remarkable advantages in recent years for printing large-area photovoltaic devices. However, the high boiling point and poor solubility of green solvents lead...
TL;DR: In this article , the authors studied the finite-time synchronization problem of delayed complex dynamical networks with impulses, where two types of impulses, namely, synchronizing impulses and desynchronizing impulses, are fully considered, respectively.
Abstract: In this article, the finite-time synchronization problem of delayed complex dynamical networks (CDNs) with impulses is studied, where two types of impulses, namely, synchronizing impulses and desynchronizing impulses, are fully considered, respectively. Since the existence of impulses makes the discontinuity of the states, which means that the classical result for finite-time stability is inapplicable in such a case, the key challenge is how to guarantee the finite-time stability and estimate the settling time in impulse sense. We apply impulsive control theory and finite-time stability theory to CDNs and establish some sufficient conditions for finite-time synchronization, where two kinds of memory controllers are designed for synchronizing impulses and desynchronizing impulses, respectively. Moreover, the upper bounds for settling time of synchronization, which depends on the impulse sequences, are effectively estimated. It shows that the synchronizing impulses can shorten the settling time of synchronization; conversely, the desynchronizing impulses can delay it. Finally, the theoretical analysis is verified by two simulation examples.
TL;DR: In this paper , the transient behavior of a wind turbine when two blades are struck simultaneously by lightning is studied, and the model is used to calculate the variation of induced overvoltages across the wind turbines during the strike.
Abstract: Wind turbines (WTs) are one of the most promising sources of sustainable energy. However, they are frequently subjected to lightning strikes resulting in downtime of WTs and loss of numerous megawatts of power generation. Studying the transient behavior of a WT when two blades are struck simultaneously by lightning is the main contribution of this article. Although the simultaneous hitting of two blades of the same WT is not occurring frequently, it is more severe than striking a single blade. Hence, assessing the transient behavior of WTs during this phenomenon is important for proper lightning protection system design. The variation of induced overvoltages across the WT during the strike is calculated using a simplified numerical model. The equivalent circuit of WT is represented in the time domain, including various WT parts starting from the blades up to the grounding system. Then, the continuous time-domain circuit is converted to a discrete time-domain circuit, and the system nodal equations are written to calculate the transient response. For checking the validity of the numerical model, a small-scale WT model is connected with an impulse generator to simulate the lightning strike in the laboratory. The measured overvoltages across the small-scale WT are found to be very close to the numerical ones at different grounding resistances, which proves the correctness of the numerical model.
TL;DR: A periodic sparse attention network is proposed to decrease the time consumption in the process of reducing the influence of random interference and enhancing the feature, and LSTM is used to extract long-term dependence features in the fault signals.
Abstract: The rolling bearing fault signals are complex time series with complex dynamic characteristics and non-uniform periodicity due to the influence of random interference, such as random impulse noise and equipment vibration. This will affect the accuracy of the diagnostis method. This paper analyses the characteristics of bearing fault signals and discussed the basic ideas of current diagnosis methods. In order to decrease the computational complexity in time series analysis process and reduce the influence of random interference in subsequent feature extraction, this paper proposes a rolling bearing fault diagnosis method base on periodic sparse attention and LSTM (PSAL) for non-uniform bearing vibration signals. According to the periodic characteristics of bearing fault, a periodic sparse attention network is proposed to decrease the time consumption in the process of reducing the influence of random interference and enhancing the feature. Then, LSTM is used to extract long-term dependence features in the fault signals. Finally, two sets of rolling bearing datasets are adopted to verify the validity and superiority of the proposed method by comparing with other methods.
TL;DR: In this paper , an Archimedes spiral antenna is proposed for partial discharge detection under fast rise time repetitive impulse voltages. But the antenna structure is optimized by a media superstrate with a high dielectric constant over the radiant surface.
Abstract: Partial discharge (PD) measurements under repetitive impulse voltages are critical for the qualification of inverter-fed motor insulation systems. Severe electromagnetic interference due to high frequency switching from power electronic devices can cause the traditional PD detection techniques of sinusoidal voltage unfeasible. This article presents the design of an Archimedes spiral antenna that can work effectively for PD detection under fast rise time repetitive impulse voltages. The antenna structure is optimized by a media superstrate with a high dielectric constant over the radiant surface. Through the optimized design, both the gains of the antenna in the 0.5–1.5 GHz frequency range and the signal-to-noise ratio for PD detection are increased substantially. Modeling and experimental results prove that the gain of the antenna can reach 2.5 dB in the frequency range of 500–900 MHz and become higher than 7.0 dB in the frequency range of 900–2.0 GHz, with a voltage standing–wave ratio smaller than 1.4. This seems to be a significant achievement for PD detection under fast rise time impulse voltages.
TL;DR: Zhang et al. as mentioned in this paper explored the effect of social presence in live streaming on customer impulse buying based on the stimulus-organism-response framework and identified pleasure and arousal as the mediation of impulse buying.
Abstract: With the proliferation of live streaming, there is evidence that online impulse buying is becoming an emerging phenomenon. Although many studies have investigated impulse buying in the context of offline shopping and business-to-consumer e-commerce, online impulse buying in live streaming has attracted little attention. In this study, we aim to explore the effect of social presence in live streaming on customer impulse buying based on the stimulus–organism–response framework. The research model presented here identifies pleasure and arousal as the mediation of impulse buying in live streaming. We use the AMOST and IBM SPSS PROCESS software to estimate our model based on data at the minute level from 189 customers, who watched live streaming in the past three months. The results suggest that the social presence of the broadcaster and the social presence of the live streamer positively affect impulse buying directly and indirectly via pleasure and arousal, promoting consumer online impulse buying in live streaming, but the social presence of the viewers has no significant effect on pleasure and arousal. For practice, our results can help policymakers and operators of the live streaming platform alleviate impulse buying in the digital world.
21 Feb 2022
TL;DR: In this paper , a classification dataset for shallow water propagation is generated with the threshold limits of range and frequency of each propagation model, and an GUI is created that classifies the required propagation model and simulate the model with the inputs of range, frequency and sound velocity profiles.
Abstract: The acoustic medium in ocean has high complications due to its non-homogenous property. The speed of sound in the medium plays a significant role in acoustic computations and is more related to the density and compressibility of the propagation medium. Several acoustic propagation modelling methods that are described by wave equations are proposed for different underwater applications. The mathematical propagation models that are used widely are the empirical method (Thorp’s model), ray theory (Bellhop model), normal mode method (Kraken), wavenumber integration (Scooter), and parabolic equations (RAMGeo). The propagation models compute several parameters that include transmission loss, impulse response, arrival time, etc. with the input of the sound velocity profile and the transmission environment. The error rate of the propagation models varies with respect to the frequency, range of transmission and other parameters as well. In this paper, a classification dataset for shallow water propagation is generated with the threshold limits of range and frequency of each propagation model. Since, the limits of the propagation model are non-linear, machine learning based algorithms are proposed and validated with the data generated. Finally, an GUI is created that classifies the required propagation model and simulate the model with the inputs of range, frequency and sound velocity profiles.
TL;DR: A wave-to-wire analytical code modeling an entire wave energy converter based on the oscillating water column (OWC) technology, operating with either a Wells or an impulse turbine, was developed in this paper .
TL;DR: In this paper , the surface charge and electric field distributions of a tri-post insulator in ±800kV gas-insulated transmission line (GIL) were calculated under the superimposed dc-impulse voltage and the polarity reversal voltage.
Abstract: Surface charge and electric field distributions of a tri-post insulator in ±800-kV gas-insulated transmission line (GIL) are calculated under the superimposed dc-impulse voltage and the polarity reversal voltage. The theoretical discharge inception voltage of the tri-post insulator under the abovementioned conditions is estimated by the volume-time theory. The accumulated homocharges on the insulator surface significantly relax the electric field at the dc steady state, thus improving the theoretical discharge inception voltage under dc superimposed homopolar impulse voltage but reducing that under dc superimposed heteropolar impulse voltage. When the voltage polarity is reversed in two minutes, the intensified electric field on the insulator surface shifts from the grounded (GND) electrode toward the vicinity of the high voltage (HV) electrode, in which the maximum electric field grows by 21.4% and increases as the reversal time shortens. The micro-discharge around the particle trap may induce the accumulation of heterocharges on the insulator surface between the lower two posts, aggravating the electric field distortion in the surrounding region and degrading its insulation performance.
TL;DR: In this article , an improved Gini index (IGIGI)-based envelope analysis method named IGIgram is developed for fault diagnosis of rolling bearings. And the performance of the IGI-based method is verified on the simulation signal and railway bearing experimental signals and compared with typical sparsity measures-based envelop analysis methods and log-cycligram.
Abstract: The transient impulse features caused by rolling bearing faults are often present in the resonance frequency band which is closely related to the dynamic characteristics of the machine structure. Informative frequency band identification is a crucial prerequisite for envelope analysis and thereby accurate fault diagnosis of rolling bearings. In this paper, based on the ratio of quasi-arithmetic means and Gini index, improved Gini indices (IGIs) are proposed to quantify the transient impulse features of a signal, and their effectiveness and advantages in sparse quantification are confirmed by simulation analysis and comparisons with traditional sparsity measures. Furthermore, an IGI-based envelope analysis method named IGIgram is developed for fault diagnosis of rolling bearings. In the new method, an IGI-based indicator is constructed to evaluate the impulsiveness and cyclostationarity of the narrow-band filtered signal simultaneously, and then a frequency band with abundant fault information is adaptively determined for extracting bearing fault features. The performance of the IGIgram method is verified on the simulation signal and railway bearing experimental signals and compared with typical sparsity measures-based envelope analysis methods and log-cycligram. The results demonstrate that the proposed IGIs are efficient in quantifying bearing fault-induced transient features and the IGIgram method with appropriate power exponent can effectively achieve the diagnostics of different axle-box bearing faults.
TL;DR: Zhang et al. as mentioned in this paper proposed a theoretical framework with which to examine how live streaming affects consumers' urge to buy impulsively, and found that social presence of a live streamer, other viewers and product positively influence affective intensity.
Abstract: Abstract The rapid popularity of live streaming promotes the emergence of a new business model known as live streaming commerce. Due to high interactivity and rich-sensory stimuli, live streaming easily leads to consumers’ impulse buying. However, knowledge on impulse buying in live streaming commerce is considerably limited. Drawing on the social presence theory and cognitive-affective framework, our study proposes a theoretical framework with which to examine how live streaming affects consumers’ urge to buy impulsively. In an online survey, 267 valid responses were obtained. Results indicate that social presence of live streamer, social presence of other viewers and social presence of product positively influence affective intensity. Results also show that social presence of other viewers and social presence of product negatively influence perceived risk. Furthermore, this study proves that the urge to buy impulsively is driven by affective state (i.e., affective intensity) instead of cognitive state (i.e., perceived risk) in the live streaming commerce context. This study provides a deep understanding of the psychological mechanism underlining consumers’ impulse buying in live streaming commerce. The findings also offer suggestions for online retailers to enhance product sales.
TL;DR: In this article , a piezoelectric stick-slip actuator with the inertial block structure is presented in an attempt to achieve smooth motion under asymmetric excitation.
Abstract: A piezoelectric stick–slip actuator with the inertial block structure is presented in an attempt to achieve smooth motion. Under asymmetric excitation, the inertial block produces different inertia, which can dynamically change the normal pressure between the stator and rotor to adjust the friction. During the slip stage, the driving arm produces a deflection away from the rotor, the normal pressure between the stator and rotor can be eliminated, and the angular impulse of the moment of friction force on the rotor can be almost reduced to zero. To verify the feasibility of the prototype, finite-element method simulation is performed. On the basis of the experimental system, the output characteristics of the prototype are systematically studied. The experimental results indicate that the prototype can achieve smooth motion under large pretightening displacement. The displacement curve under the load of 2.0 kg still shows good smoothness, and the resolution is 1.56 μ rad. This article proposes a new design concept of dynamic control of the normal pressure to achieve smooth motion for piezoelectric stick–slip actuators, even under heavy-load conditions, using the inertial block structure.
01 Jun 2022
TL;DR: In this article , the Takagi-Sugeno (T-S) fuzzy impulsive control problem is investigated for a class of nonlinear positive systems with time delay, where the time delay under consideration is both in the continuous-time dynamics and at the impulsive instants, which can model practical systems more accurately.
Abstract: In this study, the Takagi-Sugeno (T-S) fuzzy impulsive control problem is investigated for a class of nonlinear positive systems with time delay. The time delay under consideration is both in the continuous-time dynamics and at the impulsive instants, which can model practical systems more accurately. An impulse-time-dependent copositive Lyapunov function (IDCLF) is constructed, and the Razumikhin technique is adopted to develop conditions that ensure the globally exponential stability of T-S fuzzy positive systems with delayed impulses. The size constraint between the impulse delay and the bound of impulsive intervals is removed. A T-S fuzzy impulsive controller is designed in terms of the solutions to certain vector inequalities that are readily solvable. Numerical examples and a practical example of lipoprotein metabolism and potassium ion transfer model are given to demonstrate the effectiveness, advantages, and practicality of the proposed results.
TL;DR: In this paper , the authors studied how external stimulus variables (anchor characteristics, online comments, logistics service quality, promotion incentive information, and promotional time limit) affected consumers' impulse buying behavior under the inner mechanism reaction factors (perceived trust and perceived value).
Abstract: The sustainability of live commerce is closely dependent on the impulse buying behavior of consumers because of its live characters compared to the traditional e-commerce mode. Hunger marketing is a widely adopted mode in live commerce, however, the influencing factors on impulse buying behavior of consumers under the mode of hunger marketing in live commerce is currently lacking. Here, based on SOR theory, we carefully studied how external stimulus variables (anchor characteristics, online comments, logistics service quality, promotion incentive information, and promotional time limit) affected consumers’ impulse buying behavior under the inner mechanism reaction factors (perceived trust and perceived value). By collecting questionnaires from 533 Chinese online consumers, we processed these data using SPSS23.0 and analyzed them using the structural equation model (SEM) generated by AMOS 25.0. The results showed that extrinsic stimulus variables (except for the promotional time limit variable) have significant positive effects on impulse buying behavior through partial or total positive effects on intrinsic mechanisms. We analyzed the reasons for all these results in detail, and thought the reason that the promotional time limit did not have a significant impact on the perceived value might be due to the rapid increase in the frequency of live commerce. Moreover, we also put forward the suggestions on the basis of these influencing factors to improve the sustainable development of live commerce.
TL;DR: In this paper , an input velocity adjustment method of the critical double impulse (DI) is presented for efficient design of viscous dampers for elastic-plastic moment frames, where the input energy to the lowest eigenmode under the critical DI is equal to those under the selected recorded ground motions.
Abstract: An input velocity adjustment method of the critical double impulse (DI) is presented for efficient design of viscous dampers for elastic-plastic moment frames. The input velocity is adjusted so that the input energy to the lowest eigenmode under the critical DI is equal to those under the selected recorded ground motions. This adjustment makes the critical DI work as the active earthquake. The response bounding property of the critical DI is supported by, (1) the multi-modal property of the critical DI, (2) the usual excitation of the lowest mode response under recorded ground motions, (3) the large proportion of the instantaneous input energy to the total input energy in the critical DI. The proposed method can treat not only pulse-like near-fault ground motions but also ground motions of random nature. To validate the proposed method, the input energies and the maximum interstory drifts under the recorded ground motions and the critical DI with the adjusted input velocity are investigated for elastic single-degree-of-freedom (SDOF) models, elastic proportionally damped MDOF models, and elastic-plastic proportionally damped MDOF models. The optimization method presented in the previous paper is extended so that the critical DI can be treated for the design of viscous dampers for elastic-plastic moment frames.
TL;DR: In this article , an improved Nakamura model was developed to convert dynamic impedance to an impulse response function, and the causes and distribution rules of repeated phase angles were investigated based on the traveling time-lag effect, rendering the improved method more robust.
TL;DR: In this paper , a sliding-mode control (SMC) of linear uncertain systems with impulse effects is considered, and a suitable integral SMC law with switching feedback gains is constructed to guarantee the reachability of the designed sliding surface in a finite time.
Abstract: This article addresses the problem of sliding-mode control (SMC) of linear uncertain systems with impulse effects. The difficulty in solving such problem lies in that the continuity property of the well-used linear sliding function is lost under the intermittent impulsive action. In order to overcome this difficulty, a piecewise linear sliding function considering the dynamics properties of impulses is introduced, which turns out to be continuous along the trajectories of the impulsive system. Then, a suitable integral SMC law with switching feedback gains is constructed to guarantee the reachability of the designed sliding surface in a finite time. The resulting sliding-mode dynamics is modeled by an impulsive switched system whose stability is analyzed by applying a piecewise discontinuous Lyapunov function. Next, a sufficient condition for the existence of integral SMC law is derived in terms of linear matrix inequalities. Finally, a numerical example with several different types of impulses is provided to validate the theoretical results, which shows that the switching gain-based design contributes to the robustness of the sliding-mode controller.
TL;DR: In this paper , an analytical wave-to-wire model of an oscillating water column (OWC) device for the preliminary optimization of these systems for a small installation in a moderate wave climate in the Mediterranean Sea is presented.
TL;DR: In this paper , the intralayer synchronization on a multiplex network (i.e., a set of networks connected through interlayer edges) via the pinning impulsive control method is studied.
Abstract: These days, the synchronization of multiplex networks is an emerging and important research topic. Grounded framework and theory about synchronization and control on multiplex networks are yet to come. This article studies the intralayer synchronization on a multiplex network (i.e., a set of networks connected through interlayer edges), via the pinning impulsive control method. The topologies of different layers are independent of each other, and the individual dynamics of nodes in different layers are different as well. Supra-Laplacian matrices are adopted to represent the topological structures of multiplex networks. Two cases are considered according to impulsive sequences of multiplex networks: 1) pinning controllers are applied to all the layers simultaneously at the instants of a common impulse sequence and 2) pinning controllers are applied to each layer at the instants of distinct impulse sequences. Using the Lyapunov stability theory and the impulsive control theory, several intralayer synchronization criteria for multiplex networks are obtained, in terms of the supra-Laplacian matrix of network topology, self-dynamics of nodes, impulsive intervals, and the pinning control effect. Furthermore, the algorithms for implementing pinning schemes at every impulsive instant are proposed to support the obtained criteria. Finally, numerical examples are presented to demonstrate the effectiveness and correctness of the proposed schemes.