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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]

In geometry processing, symmetry is a universal type of high-level structural information of 3D models and benefits many geometry processing tasks including shape segmentation, alignment, matching, and completion. Thus it is an important problem to analyze various symmetry forms of 3D shapes. Planar reflective symmetry is the most fundamental one. Traditional methods based on spatial sampling can be time-consuming and may not be able to identify all the symmetry planes. In this article, we present a novel learning framework to automatically discover global planar reflective symmetry of a 3D shape. Our framework trains an unsupervised 3D convolutional neural network to extract global model features and then outputs possible global symmetry parameters, where input shapes are represented using voxels. We introduce a dedicated symmetry distance loss along with a regularization loss to avoid generating duplicated symmetry planes. Our network can also identify generalized cylinders by predicting their rotation axes. We further provide a method to remove invalid and duplicated planes and axes. We demonstrate that our method is able to produce reliable and accurate results. Our neural network based method is hundreds of times faster than the state-of-the-art methods, which are based on sampling. Our method is also robust even with noisy or incomplete input surfaces. [ABSTRACT FROM AUTHOR]

The multilayered parallel-plate structure (MPPS) is a typical structure in microwave engineering. In numerical simulation, MPPS is usually modeled by an infinitely large planarly layered medium (PLM) to simplify the computation. For a realistic microwave circuit, however, the substrate is always finite in spatial extent, i.e., it is a finite-sized MPPS (FS-MPPS). To address this issue, a novel surface integral equation (SIE) formulation is proposed for the efficient simulation of FS-MPPS. In this article, the surface equivalence principle is first revisited. For the exterior and interior problems, different Green’s functions are utilized. In particular, the common homogeneous-medium Green’s function is used for the exterior homogeneous region, whereas the layered-medium Green’s function (LMGF) is applied for the interior multilayered structure. In this manner, FS-MPPS is no longer directly approximated by the infinite PLM model, but instead, it is modeled accurately by SIE whose integration kernel is derived from PLM. Finally, a PMCHWT SIE is established for the electromagnetic analysis of FS-MPPS. Due to the finite nature of the inner problem, the setting of PLM and LMGF is not unique. This nonuniqueness is studied in theory and verified by numerical simulation. It is revealed that such a nonuniqueness of the setting of the inner problem does not change the uniqueness of the final solution. To validate the proposed approach, a multidomain FS-MPPS and an FS-MPPS with embedded dielectric structures are investigated. Compared with the conventional brute-force SIE methods for FS-MPPS, where all the interfaces of the layered structure should be discretized and assigned with degrees of freedom (DOFs), the proposed method is more succinct and efficient. [ABSTRACT FROM AUTHOR]

A novel hydraulic fracture scattering simulation method in the hydrocarbon diagnosis is developed in this article. The traditional thin dielectric structure-based surface integral equation (TDS-SIE) is adopted for accurate and stable fracture scattering analysis. To improve the low simulation efficiency of conventional TDS-SIE, a higher order TDS-SIE (HO-TDS-SIE) is developed in this article. The junction vector bases are defined to extend TDS-SIE for the branched fractures. Moreover, the matrix normalization method is adopted to improve the conditioning of impedance matrices and accelerate the convergence rate. The excellent performance of this new HO-TDS-SIE solver for complex hydraulic fracture and network is validated by numerical experiments. To best of our knowledge, this is the first time to extend TDS-SIE into higher order scheme for accurate fracture scattering simulation. [ABSTRACT FROM AUTHOR]

A deep learning based approach is proposed to accurately recover shock signals measured from a damaged high-g accelerometer without modifying the hardware. We first conducted shock tests and collected a large dataset of shock signals with different levels of acceleration by using an efficient experimental apparatus. The training data is composed of a pair of signals simultaneously obtained from a faulty accelerometer and a high-end accelerometer (served as the ground truth). A customized autoencoder neural network is designed and trained on this dataset, aiming to map the faulty signals to their reference counterparts. Experimental results show that, with the help of deep learning, shock signals can be accurately recovered from the faulty measurements. Compared with conventional approaches that require diagnosing and replacing faulty parts, the proposed data-driven method demonstrates a highly promising solution that allows recovering corrupted signals without introducing extra work to upgrade the hardware at almost zero cost. The dataset and code of this work are made publicly available on GitHub at https://github.com/hope-yao/Sensor_Calibration. [ABSTRACT FROM AUTHOR]

This article proposes an enhanced active disturbance rejection control (ADRC) method for the attitude deformation system of a self-developed mobile robot in conjunction with evolutionary game theory-based pigeon-inspired optimization (EGPIO). To achieve precise control of the object, EGPIO is employed as an automatic tuning mechanism for ADRC, and simultaneously improves the rapidity and robustness of the controller. In this novel algorithm, individuals in pigeon-inspired optimization (PIO) adjust their strategies dynamically as the evolutionary game proceeds so as to promote the adaptability of the original PIO. Thus, the optimal solutions calculated by EGPIO will be adopted as the main parameters of ADRC to control the mobile robot. The effectiveness of the novel controller is validated by a series of simulations, including cases with normal conditions and situations with disturbances. Experimental results indicate that the scheme we designed possesses better control performances and shows attractive advantages for efficiency and fault tolerance compared with conventional ADRC. [ABSTRACT FROM AUTHOR]

Owing to the development of soft electronics enabled from liquid metal, flexible and wearable sensors have been attracting more and more interest recently. So far, several types of liquid metal sensors based on soft substrate have been gradually developed. However, there is still too much space to explore regarding fabrication efficiency including resolution etc. which in fact determines further development and applications of liquid-metal flexible sensors. In this article, we proposed and demonstrated a novel method to fabricate liquid-metal circuits on PDMS (Polydimethylsiloxane) by spraying and wiping processing, which simultaneously offers simpler manufacturing process and smaller feature size as compared with existing approaches. According to various desired needs, the PDMS substrate can be prepared with specifically designed micro-channels in advance and then liquid metal entity can be patterned via subsequent spraying and wiping. As experiments indicate, the whole process is quite implementable and convenient. Except for PDMS, we further showed that PDMS mixed up with Ecoflex can also serve as a benign substrate. In order to illustrate the applications of this technique, we successfully produced several typical functional circuits and tested their working performances. Their roles to develop further electrical or thermal resistive sensors were discussed. Overall, the feature size with high reliability has reached 50 μm. The present method is expected to contribute to the development of liquid-metal sensors with high resolution and sensitivity. [ABSTRACT FROM AUTHOR]

Lumen, chromaticity, and correlated color temperature CCT are the three main performance indicators of failure of high-power white light-emitting diodes (LEDs) (HPWLEDs). The existing data-driven (DD) method to predict the life of LEDs often considers that three performance indicators are independent, or only one or two performance indicators are used for prediction, which may not be accurate enough. To solve this problem, a method based on Archimedean Copula function is proposed to describe the correlation of multiple performance indicators. The test data reported from LUXEON is used as an example to establish a 3-D life prediction model by combining the thresholds of three performances to predict the life of LEDs, and the application of Copula function is explained. The results show that there is a little influence on life prediction of LEDs among the different Copula function structures, while the difference between considering single performance and multi-performance is obvious. The mean time to failure (MTTF) of which is proven to be more conservative than the L70 life predicted by the conventional method. [ABSTRACT FROM AUTHOR]

IP flow mobility (IFOM) enables a user equipment to offload data traffic at the IP flow level. Although the procedure of IFOM-based flow offloading has been specified by 3GPP, how many IP flows should be offloaded and when offloading should be performed are not defined. Consequently, IP flows may be routed to a target access network that has a strong signal strength but with backhaul congestion or insufficient access capability. In this paper, we propose two algorithms, referred to as proportional offloading (PO) and proportional and preemption-enabled offloading (PPO), respectively, for IP flow offloading in hybrid cellular and wireless local area networks. The PO algorithm decides an optimal proportion of IP flows, which could be offloaded by considering available resources at the target access network. In the PPO algorithm, both service continuity and network utilization are taken into consideration. Furthermore, a detailed analytical model is developed in order to evaluate the behavior of the proposed algorithms. The analytical model is validated through extensive simulations. The results show that by dynamically adjusting the percentage of traffic flows to be offloaded, PO can reduce blocking probability and increase resource utilization. PPO further improves the performance at the cost of slightly higher offloading overhead. [ABSTRACT FROM AUTHOR]

This paper presents a novel accurate and stable current and charge integral equation (CCIE) solver for the low-frequency scattering of penetrable objects in layered medium (LM). To the best of our knowledge, this is the first time to extend CCIE into LM simulations at low frequency. In order to integrate the matrix-friendly LM Green’s functions (LMGFs) into CCIE, we have rederived them to define new quasi-vector/scalar potentials, which are able to annihilate the frequency singularity in the original LMGFs. Moreover, an effective preconditioner is adopted to improve the conditioning of impedance matrices. In comparison with other perconditioners, this method performs much better. The excellent performance of this new CCIE solver is then demonstrated by numerical experiments. [ABSTRACT FROM AUTHOR]

In evolved multimedia broadcast/multicast service (eMBMS), service continuity enables users move from one cell to another without interrupting eMBMS service. Unlike traditional handover in unicast transmission, an user equipment can receive eMBMS service in either unicast or multicast mode. In this paper, we point out a new handover failure problem in eMBMS due to the miss of rekeying information. We first take a close look at the new handover scenarios. We then investigate the problem by using comprehensive mathematical models. Our models provide insights on the new handover problem and introduce theoretical guidelines for mobile operators to design and optimize their networks without wide deployment to save cost and time. Moreover, we propose a solution to combat against the handover failure. Both the simulation and analytical results demonstrate that the impacts of the eMBMS handover failure are reduced significantly. In this paper, we present a systematic way to investigate the handover failure problem in eMBMS. [ABSTRACT FROM AUTHOR]

The correlated color temperature (CCT) is one of the performance indicators of color shift failure of the high-power white light-emitting diodes (HPWLEDs). The prognostics for CCT shift of HPWLEDs using deterministic or statistical models usually generate a considerable amount of uncertainties by assuming the degradation model of CCT is a deterministic exponential function, which may not be accurate. To overcome this problem, a stochastic process model based on gamma process is established to present the distribution of CCT maintenance lifetime with the probability density function and the cumulative distribution function. The test data reported from LUXEON was used as an example to demonstrate the utilization of the gamma process model. The mean time to failure of which was proved to be more conservative than the L70 lifetime predicted by the conventional method. The CCT shift appears to have a period of nonmonotonic seasoning stage, whereas the gamma process is only applicable to the monotonic degradation. Aiming at this problem, a unified analytical method was established based on generalized Eyring model to estimate seasoning stage under various conditions. The results of which were proved to be reliable. [ABSTRACT FROM AUTHOR]

We present an efficient nonconformal-mesh discontinuous Galerkin (DG) method for elastic wave propagation in viscous media. To include the attenuation and dispersion due to the quality factor in time domain, several sets of auxiliary ordinary differential equations (AODEs) are added. Unlike the conventional auxiliary partial differential equation-based algorithm, this new method is highly parallel with its lossless counterpart, thus requiring much less time and storage consumption. Another superior property of the AODE-based DG method is that a novel exact Riemann solver can be derived, which allows heterogeneous viscoelastic coupling, in addition to accurate coupling with purely elastic media and fluid. Furthermore, thanks to the nonconformal-mesh technique, adaptive hp-refinement and flexible memory allocation for the auxiliary variables are achieved. Numerical results demonstrate the efficiency and accuracy of our method. [ABSTRACT FROM PUBLISHER]

A novel hybrid method is developed for the flexible and accurate electromagnetic simulation of penetrable objects in a layered medium (LM). In this method, the original complex simulation domain is first divided into several subdomains, following the spirit of divide-and-conquer. Each subdomain is then meshed and solved independently, where nonconformal mesh is inevitable. The Riemann type transmission condition is utilized at the interfaces of each subdomain to correctly exchange information so that the solutions of all subdomains converge rapidly to the real solution of the original problem. More specifically, in our method, the surface integral equation (SIE) combined with the LM Green’s functions (LMGFs) is adopted for the boundary subdomain, while the finite-element method (FEM) and the spectral element method (SEM) are employed for all the other interior dielectric subdomains. The SIE with LMGFs truncates the simulation domain tightly within the object itself, which drastically decreases the number of unknowns. The interior subdomains are modeled by either FEM or SEM, depending on the geometry and material property of each subdomain. To further enhance the simulation capability, higher order approaches are adopted for all the subdomain solvers in this hybrid method. Several numerical examples are demonstrated, where a high convergence and accuracy of this method is observed. This paper will serve as an efficient and flexible simulation tool for the applications of geophysical exploration. [ABSTRACT FROM PUBLISHER]

It is essential to model channel holding time (CHT), cell residence time (CRT), and handoff rate for performance analysis and algorithm evaluation in mobile cellular networks. The problem has been extensively studied in the past for circuit-switched (CS) cellular networks. However, little research has been done on packet-switched (PS) cellular networks. Unlike that a call occupies a dedicated channel during its whole lifetime in CS networks, an active session in PS networks occupies and releases channels iteratively due to discontinuous reception (DRX) mechanism. In this paper, we investigate the key quantities in PS cellular networks. We present a set of comprehensive new models to characterize the quantities and their relationship in PS networks. The models shed light on the relationship between CHT and CRT and handoff rate. The analytical results enable wide applicability in various scenarios and therefore have important theoretical significance. Moreover, the analytical results provide a quick way to evaluate traffic performance and system design in PS cellular networks without wide deployment, which can save cost and time. [ABSTRACT FROM AUTHOR]

3GPP introduced the key management mechanism (KMM) in evolved multimedia broadcast/multicast service (eMBMS) to provide forward security and backward security for multicast contents. In this paper, we point out that KMM may lead to frequent rekeying and re-authentication issues due to eMBMS’s characteristics: 1) massive group members; 2) dynamic group topology; and 3) unexpected wireless disconnections. Such issues expose extra load for both user equipment (UE) terminals and mobile operators. It seems prolonging the rekeying interval is an intuitive solution to minimizing the impact of the issues. However, a long rekeying interval is not considered the best operational solution due to revenue loss of content providers. This paper quantifies the tradeoff between the load of the UEs and the operators as well as the revenue loss of the content providers. Moreover, we emphasize how essential this rekeying interval has impacts on the problems. Using our proposed tradeoff model, the operators can specify a suitable rekeying interval to best balance the interest between the above three parties. The tradeoff model is validated by extensive simulations and is demonstrated to be an effective approach for the tradeoff analysis and optimization on eMBMS. [ABSTRACT FROM PUBLISHER]

In order to directly utilize the dyadic Green’s functions in surface integral equations (SIEs), a novel double-arctan transformation for nearly hypersingular integrals is proposed in this communication. This new transformation is flexible and applicable to nearly hypersingular integrals in the forms of \hat R\hat R/R^3 , \hat R/R^3^^ , and 1/R^3 over the curved surfaces by a fully numerical method. With the help of the sigmoidal transformation to improve the stability of this new singularly handling method, there results an efficient solution for the third-order near-singularity problems in SIEs. Moreover, the proposed method is also effective for the lower orders of the nearly singular integral kernels. With typical testing cases, the performance of this method is fairly evaluated, and its validity and stability is well demonstrated. [ABSTRACT FROM PUBLISHER]

The thin dielectric sheet-based surface integral equation (SIE) method is introduced to the accurate simulation of fracture scattering, which is an important and challenging topic in hydrocarbon exploration. In the proposed method, the equivalent volume current is decomposed into the equivalent surface current and the constant normal current. With this decomposition, the D-field volume integral equation degenerates into the SIE, which makes our proposed method stable, accurate, and efficient at low frequency. Numerical results have demonstrated its excellent performance. [ABSTRACT FROM PUBLISHER]

Accurate and efficient prediction of electromagnetic scattering from inhomogeneous objects in layered medium is one of the most challenging issues in engineering applications. This paper presents the first 3-D higher order hybrid finite-element method (FEM) and method of moments (MoM) for the accurate modeling of inhomogeneous dielectric objects in multilayered medium. The main challenges of this paper include: 1) the integration of these algorithms for layered medium and 2) the higher order computational approach involved in layered medium for high efficiency. In the proposed method, the MoM with the layered medium dyadic Green’s function is used as the exact radiation boundary condition in an inhomogeneous background, and the FEM is applied to model the inhomogeneous objects. Furthermore, the higher order maximally orthogonal basis functions with curl-conforming and divergence-conforming properties are used in the FEM and MoM, respectively to improve the modeling capability of this algorithm. For 3-D inhomogeneous objects scattering in multilayered medium, this new method requires a much more tightly truncated simulation domain than the traditional FEM, and provides much higher flexibility than the pure surface integral equation method. Finally, some numerical results are provided to validate the accuracy, efficiency, and flexibility of this method. [ABSTRACT FROM AUTHOR]