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In this letter, we present a novel fast direct solver based on a modified hierarchically off-diagonal low-rank (M-HODLR) matrix format with higher order basis functions for analyzing electromagnetic scattering by electrically large objects. The M-HODLR matrix compresses the far-group submatrices by an extended admissibility condition, which enhances the efficiency and accuracy of the original HODLR. To further alleviate the burden of the fast direct solution of the conventional surface integral equation (SIE), the higher order hierarchical vector basis (HOHVB) functions defined over a curved surface are employed. To account for HOHVB, an efficient assembly scheme based on patch coupling is developed to accelerate the adaptive across approximation implementation in M-HODLR. The proposed method can significantly reduce the computational time and memory cost of a conventional SIE solver. Several numerical examples are presented to validate the accuracy and efficiency of the proposed method in solving electrically large objects. Owing to the characteristics of HOHVB, different patch sizes or basis functions with different orders can be chosen according to the local geometry of the object. Therefore, the proposed method is very appealing for large- and multiscale simulations. [ABSTRACT FROM AUTHOR]

A new approach for synthesizing wideband frequency-invariant (FI)-shaped patterns is presented. This method is a significant extension of the original iterative spatiotemporal Fourier transform (STFT) method that only deals with wideband FI pencil-beam patterns. Based on the original method, the wideband pattern can be regarded as a spatiotemporal spectral distribution, and the relationship between the spatiotemporal spectral distribution and finite-impulse-response (FIR) filter coefficients can be built as an STFT, which can be efficiently calculated by using 2-D fast Fourier transform (2-D-FFT). To achieve desired FI-shaped pattern performance, the spatiotemporal spectral distribution is iteratively adjusted by two new techniques called wideband pattern shaping and linear phase response (LPR)-based modification. Different from the constant phase response (CPR) processing in the original iterative STFT method, the LPR-based modification uses more relaxed phase requirements, thus releasing much more degrees of freedom. Numerical results show that the proposed method is effective even for very complicated pattern requirements, and it is very efficient in terms of both computation and storage. Besides, the proposed method can take into account the effects of frequency-variant antenna element patterns and mutual coupling in the periodic array structure. [ABSTRACT FROM AUTHOR]

A symmetry relation of the integral operators in a layered medium proved by the reciprocal theory can be applied to improve the accuracy of the magnetic-field integral equation (MFIE). Based on the symmetric layered medium Green’s function, the normal vector can be transferred into the inner integral to keep the field integral as the inner integral of the elements in the impedance matrix. When discretized by the divergence-conforming function, this field-extracted scheme shows better performance than the classic expression in accuracy. Meanwhile, this form of expression can be applied in the combined-field integral equation (CFIE). Several numerical results are provided to validate the formulation of the symmetry relations from the layered medium Green’s function to the impedance matrices and to reveal its advantages in enhancing the accuracy of the field-extracted form of MFIE. [ABSTRACT FROM AUTHOR]

Fault prognosis based on single model is generally inaccurate due to the varying working conditions. A multistage fault prognosis methodology combining stage identification with Bayesian networks (BNs) and time series approach with particular emphasis on the autoregressive moving average (ARMA) model is proposed to solve this problem. In the first stage, degradation data are identified, and outliers are marked by the Euclidean distance. Degenerate attributes of outliers are finely identified by BNs and matched to the corresponding model. In the second stage, the ARMA model is used for prognosis according to the results of the fine identification. Subsequently, the double-precision identification and ARMA submodel prognosis are carried out alternately throughout the prognosis process. Three degradation types of permanent magnet synchronous motor are simulated to verify the applicability of the method. Result shows that it can track the changes in the degradation in time and obtains better results. [ABSTRACT FROM AUTHOR]

Unlike the conventional facial expressions, micro-expressions are involuntary and transient facial expressions capable of revealing the genuine emotions that people attempt to hide. Therefore, they can provide important information in a broad range of applications such as lie detection, criminal detection, etc. Since micro-expressions are transient and of low intensity, however, their detection and recognition is difficult and relies heavily on expert experiences. Due to its intrinsic particularity and complexity, video-based micro-expression analysis is attractive but challenging, and has recently become an active area of research. Although there have been numerous developments in this area, thus far there has been no comprehensive survey that provides researchers with a systematic overview of these developments with a unified evaluation. Accordingly, in this survey paper, we first highlight the key differences between macro- and micro-expressions, then use these differences to guide our research survey of video-based micro-expression analysis in a cascaded structure, encompassing the neuropsychological basis, datasets, features, spotting algorithms, recognition algorithms, applications and evaluation of state-of-the-art approaches. For each aspect, the basic techniques, advanced developments and major challenges are addressed and discussed. Furthermore, after considering the limitations of existing micro-expression datasets, we present and release a new dataset — called micro-and-macro expression warehouse (MMEW) — containing more video samples and more labeled emotion types. We then perform a unified comparison of representative methods on CAS(ME) $^2$ 2 for spotting, and on MMEW and SAMM for recognition, respectively. Finally, some potential future research directions are explored and outlined. [ABSTRACT FROM AUTHOR]

A quasi-mixed-potential layered medium Green’s function (QMP-LMGF) is proposed for non-Galerkin surface integral equation (SIE) formulations in the modeling of homogeneous dielectric objects in layered medium. The formulation is derived based on the pilot vector potential approach. In this method, the field-type LMGF in the $L$ -operator is decomposed into two parts, a “vector potential” term in a dyadic form, and a “scalar potential” term in a vector form, to represent the field components from current and charge sources, respectively. Since the proposed two potential terms (vector potential and scalar potential) do not satisfy the Lorenz gauge, we term them as quasi-mixed-potentials. The property of the two potentials is investigated to reveal that the proposed QMP-LMGF is compatible with the vector and scalar potentials in free space. Moreover, due to the continuity of the integration kernels across the interfaces, undesired line integrals are absent in the proposed QMP-LMGF when the objects are straddling different layers. Three popular non-Galerkin SIEs for dielectric objects in layered medium are studied, and the corresponding numerical results are demonstrated to validate the proposed method. [ABSTRACT FROM AUTHOR]

We propose to suppress high-power microwave pulses (HPMPs) using nonlinear dispersion and filtering natures of spoof surface plasmon polaritons (SSPPs). Frequency components of a short HPMP are distributed in time domain due to different group velocities and partly cutoff on SSPP transmission lines (TLs), leading to peak suppression of HPMP. To illustrate the protection mechanism in real microwave engineering, an SSPP mono-pulse antenna is designed. Sum and difference beam functions of the antenna are demonstrated by both simulations and experiments. For easy comparison, a microstrip mono-pulse antenna is also fabricated. HPMP incidences from the main lobe directions of the sum beam and difference beam are considered. Compared to the microstrip antenna, obvious suppression of HPMPs is observed in the SSPP mono-pulse antenna in different cases, which verifies the better performance to prevent HPMP damages by SSPPs. The proposed technology to suppress HPMPs by using SSPPs can find wide applications in radar and communication systems in the electronic warfare environment. [ABSTRACT FROM AUTHOR]

Preventive maintenance (PM) activities in battery energy storage systems (BESSs) aim to achieve a better status in long-term operation. In this article, we develop a reinforcement learning-based PM method for the optimal PM management of BESSs equipped with prognostics and health management capabilities. A multilevel PM framework is established to generate a PM action strategy considering costs, capacity, and reliability simultaneously. Finite costs are the constraints, and reliability is the objective according to capacity degradation, respectively. The proposed PM agent with an integrated Monte Carlo tree search and a deep neural network (DNN) utilizes the state-of-health information of large-scale batteries in the BESS and selects optimal maintenance actions. The DNN is used as the state-action value function to extend the ability to address PM problems with large state-action spaces. The case of a BESS with 9 × 12 × 4 batteries in a fleet is simulated via Python. The results show that the PM agent can achieve efficient and steady decision-making proficiency in BESS PM management. [ABSTRACT FROM AUTHOR]

A novel triaxis static force sensor that uses lead zirconate titanate (PZT) ceramic rings is proposed. The actuator ring is driven at the resonance frequency of the thickness vibration mode to generate ultrasonic waves in the detector rings. The electric potential between the top and bottom surfaces of the detector ring due to the direct piezoelectric effect is measured. The sensing mechanism is based on the variation of the compliance coefficient with the applied force. The bolt-clamped Langevin transducer is the most widely used ultrasonic actuator in ultrasonic machining. The proposed design composed of two PZT ceramic rings imparts triaxis static force sensing capability to the Langevin transducer without the use of external components. The statics model, relationship between stress and the compliance coefficient, and decoupling matrix were derived to estimate the forces on the tool tip based on the voltages at the electrodes on the detector ring. The mean differences between the calculated and experimental results in terms of ${F} _{\textbf {x}}$ , ${F} _{\textbf {y}}$ , and ${F} _{\textbf {z}}$ were 1.92%, 2.54%, and 4.26%, respectively, the full range of ±150 N. The experiments were conducted using different weights and a multiaxis force reference sensor. [ABSTRACT FROM AUTHOR]

In this paper, we present a multi-functional terahertz metamaterial device based on the gold and vanadium dioxide (VO2). Availing of the phase transition characteristic of VO2, the switchable performance between perfect absorption and broadband asymmetric transmission (AT) can be realized. When VO2 acts like a metal, the proposed metamaterial device behaves as a selectively perfect absorber for linearly polarized lights. By transforming the phase of VO2 into isolating state, broadband AT with high efficiencies over 90% can be achieved in the region from 1.5 THz to 2.5 THz. Moreover, perfect polarization conversion can be simultaneously realized associated with the AT effect. The Fabry-Pérot-like cavity model and the electric field distributions are employed to explain the physical mechanism of the above phenomena. Besides, the proposed metamaterial shows a high tolerance to the incident angle for achieving perfect absorption and broadband AT effect. Our designed device may provide a new avenue for developing multi-functional metamaterial devices in the THz region. [ABSTRACT FROM AUTHOR]

A novel method is presented to efficiently synthesize linearly polarized shaped patterns for antenna arrays mounted on complex platforms surrounded with many scatters. The vectorial active element patterns (Vec. AEPs) are adopted to include the mutual coupling and complex platform effect. The vectorial least-square (LS) active element pattern expansion (Vec. LSAEPE) method is developed to approximate each Vec. AEP as the radiation from a virtual subarray with identical element patterns, so that the fast Fourier transform (FFT) can be utilized to efficiently perform the forward and backward transformations between the excitation distribution and the vectorial array pattern including mutual coupling. An energy-based weighted averaging method is introduced to merge the excitation vectors obtained from copolarization (CoP) and cross-polarization (XP) pattern synthesis in each iteration and consequently the obtained final excitation vector can simultaneously meet both the CoP and XP pattern requirements. The method is called the iterative Vec. LSAEPE-FFT significantly extends the FFT-based synthesis technique to be capable of controlling the CoP main lobe shape, sidelobe distribution, and the XP level. Three examples for synthesizing different shaped patterns for different antenna arrays on complex platforms are conducted to validate the effectiveness of the proposed method. A comparison with some other representative methods is also provided to verify the advantages of the proposed method in both accuracy and efficiency. [ABSTRACT FROM AUTHOR]

An efficient improved spectrum integral method (ISIM) is proposed to accelerate the scattering simulation of cuboid object by method of moment (MoM) in multiplanar layered medium (LM). The layered medium Green’s functions (LMGFs) are studied and decomposed into transmission and reflection terms, which hold the translational invariance and reverse translational invariance, respectively. By virtue of the (reverse) translational invariance of LMGF from the uniform square grids on the surface of the cuboid object, most of the coupling between the expanding basis functions and the testing basis functions can be represented by two kinds of submatrices, i.e., the Toeplitz matrix when transmission term is involved, and the conjugate Toeplitz matrix when reflection term is involved. Moreover, the submatrix coupling the expanding/testing basis functions defined on the edges with those defined on the parallel surfaces/edges is also extended to the (conjugate) Toeplitz matrixes. This will significantly alleviate the heavy computation and memory burden from the conventional SIM. With the improved operations on the basis functions associated with the edges of the cuboid object, the proposed ISIM in LM can reach the computational complexity as low as ${O}$ (${N} ^{1.5}$ log(N)) in the matrix vector production, while the computational complexity of matrix filling and the memory requirement are both ${O}$ (${N}^{1.5}$). Moreover, compared with conventional SIM, both theoretical analysis and numerical results demonstrate that the memory requirement and matrix filling time are dramatically decreased. [ABSTRACT FROM AUTHOR]

Learning discriminative and invariant feature representation is the key to visual image categorization. In this article, we propose a novel invariant deep compressible covariance pooling (IDCCP) to solve nuisance variations in aerial scene categorization. We consider transforming the input image according to a finite transformation group that consists of multiple confounding orthogonal matrices, such as the D4 group. Then, we adopt a Siamese-style network to transfer the group structure to the representation space, where we can derive a trivial representation that is invariant under the group action. The linear classifier trained with trivial representation will also be possessed with invariance. To further improve the discriminative power of representation, we extend the representation to the tensor space while imposing orthogonal constraints on the transformation matrix to effectively reduce feature dimensions. We conduct extensive experiments on the publicly released aerial scene image data sets and demonstrate the superiority of this method compared with state-of-the-art methods. In particular, with using ResNet architecture, our IDCCP model can reduce the dimension of the tensor representation by about 98% without sacrificing accuracy (i.e., < 0.5%). [ABSTRACT FROM AUTHOR]

A novel electromagnetic modeling method for multidomain planar layered medium (MD-PLM) by surface integral equation (SIE) is proposed. The MD-PLM refers to the whole space that is separated into multiple PLM volumes, e.g., the infinite-sized PLM background with inserted finite PLM objects or multilayered parallel-plate structures. In the conventional SIE method for this scenario, only the exterior domain is considered as PLM that is modeled by layered medium Green’s functions (LMGFs), while the interior domain is treated by the multidomain homogeneous SIE. However, in this work, the surface equivalence formulation for this special scenario is reestablished by the LMGFs. Then, both the exterior and interior domains are considered as PLM that is modeled by the corresponding LMGFs and SIE in each subdomain. As a result, only the boundary of each sub-PLM domain is required to be discretized rather than the interfaces of each interior medium, which is different from the way in conventional SIE. Consequently, compared with the conventional SIEs, the proposed method can reduce a large quantity of unknowns and significantly increase the efficiency by reducing the memory consumption. By some numerical examples, the performance of this method is evaluated and compared with the conventional methods. The validity and efficiency of the newly proposed method are also well demonstrated in the examples. [ABSTRACT FROM AUTHOR]

A higher order current and charge integral equation (CCIE) approach is developed for accurate electromagnetic scattering analysis of dielectric objects for a wide frequency band, that is from extremely low frequency to microwave frequency. Compared to the conventional CCIE method, its accuracy has been considerably improved by expanding the currents and charges using high-order hierarchical vector basis functions and higher order orthogonal scalar polynomials, respectively. The proposed higher order approach retains whole-frequency-range stability as the traditional low-order counterpart, but characterized with enhanced accuracy and higher convergence rate. Moreover, the consistency of the basis functions’ expansion order in currents and charges is not mandatorily required, which further increase the flexibility in electromagnetic modeling. The scattered fields of penetrable objects are analyzed to validate the effectiveness of this new higher order CCIE, as well as investigate its accuracy, stability, and flexibility. [ABSTRACT FROM AUTHOR]