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In the application of integrity monitoring of Global Navigation Satellite System (GNSS)/Inertial Navigation System integrated navigation system in complex environments, such as vegetation covered areas, the Kalman filtering (KF) has the disadvantages of low positioning precision, poor performance of fault identification and error bounds. This study proposes an integrity monitoring method based on dynamic fading filter optimisation. According to the real‐time updates of filtering innovation, a fading filtering algorithm is designed, which can adjust the fading factor dynamically. The dynamic fading filtering algorithm is then combined with the fault identification algorithm, which integrates chi‐square and multiple solution separation. An optimisation strategy of setting a fading period to speed up the filter convergence is proposed. The simulation results show that compared with the KF, the dynamic fading filtering reduces the standard deviations of positioning errors by 26%, 39%, and 26%, respectively, in the east, north and up directions. By reducing the filter convergence period, the proposed dynamic fading filtering can enhance the accuracy of the identification results when the subsequent GNSS fault is minor. It can shorten the identification time to about 20% when the subsequent fault is large. The dynamic fading filtering can also limit the state errors below the bounds correctly.

In this study, the joint design of discrete phase transmit sequences and receive filters with the low peak sidelobe level and integrated sidelobe level in radar systems is considered. The problem is formulated as a minimisation of the peak (integrated) sidelobe level, forcing a unimodular discrete phase constraint at the design stage. To deal with the resulting non‐convex and in general the NP‐hard optimisation problem, an iterative method based on the alternate optimisation approach is proposed. Each iteration of the proposed method involves a non‐convex min–max problem to be solved. In addition, a sequential rank‐one constraint relaxation framework is proposed to initialise the procedure, each iteration of which requires the solution of a convex problem. Simulation results show that using the proposed framework for jointly finding transmit sequences and receive filters leads to a better peak sidelobe ratio and integrated sidelobe ratio for discrete phase sequences than the optimal mismatched filters design approach.

For improved positioning in urban canyons, this study proposes an efficient dual‐filter method integrating multi‐constellation global navigation satellite system (GNSS), an inertial navigation system (INS), a barometric altimeter and an on‐board diagnostics (OBD) module. The proposed method consists of a position‐domain (PD) Hatch filter and velocity Kalman filter. The Hatch filter is operated as the main positioning filter and the Kalman filter is operated as a sub‐filter to aid the main filter for the occasional GNSS outages. The Hatch filter combines barometric altimeter measurements with GNSS pseudorange and carrier phase measurements. The Kalman filter integrates the inertial measurement unit (IMU) measurements with GNSS Doppler shift and OBD speed measurements. A semi‐simulation method is applied for the accurate performance evaluation of the proposed method compared with the several conventional methods under deficient satellite visibility, multipath errors and cycle slips caused by urban canyons. By the test results, it is demonstrated that the proposed method can bound the positioning errors effectively by utilising low‐cost all‐weather sensors. The RMSEs of the proposed Kalman–Hatch dual‐filter algorithm were shown as 0.05, 0.19 and 0.11 m, respectively, and the maximum errors were shown as 0.16, 0.26 and 0.40 m, respectively, in the east, north and upward directions.

Feature selection plays a key role in target recognition especially for multiple combined sensors’ applications. This study presents an improved relief feature selection (Relief‐F) model to rank features for multi‐target recognition. Besides, the evaluation of the effectiveness of the method is conducted based on the following three measuring indices: feature redundancy, class separability and overall accuracy. The simulated data acquired by radar infrared combined sensors are used to verify the metrics of the proposed method. The experimental results demonstrate that the Relief‐F method reveals the best results compared to other feature selection methods, including principal component analysis and Fisher linear discriminant analysis. It indicates that Relief‐F can be an effective option for feature selection with high‐class separability and a low feature redundancy rate. Furthermore, high overall accuracy can be obtained using a relatively small amount of features selected by the Relief‐F method.

With the performance increase of convolutional neural network (CNN), the disadvantages of CNN's high storage and high power consumption are followed. Among the methods mentioned in various literature, filter pruning is a crucial method for constructing lightweight networks. However, the current filter pruning method is still challenged by complicated processes and training inefficiency. This paper proposes an effective filter pruning method, which uses the saliency of the feature map (SFM), i.e. information entropy, as a theoretical guide for whether the filter is essential. The pruning principle use here is that the filter with a weak saliency feature map in the early stage will not significantly improve the final accuracy. Thus, one can efficiently prune the non‐salient feature map with a smaller information entropy and the corresponding filter. Besides, an over‐parameterized convolution method is employed to improve the pruned model's accuracy without increasing parameter at inference time. Experimental results show that without introducing any additional constraints, the effectiveness of this method in FLOPs and parameters reduction with similar accuracy has advanced the state‐of‐the‐art. For example, on CIFAR‐10, the pruned VGG‐16 achieves only a small loss of 0.39% in Top‐1 accuracy with a factor of 83.3% parameters, and 66.7% FLOPs reductions. On ImageNet‐100, the pruned ResNet‐50 achieves only a small accuracy degradation of 0.76% in Top‐1 accuracy with a factor of 61.19% parameters, and 62.98% FLOPs reductions.

Depth filters used in multistage filter systems adeptly clean the intake air of gas turbines, preventing damage and increasing performance. However, estimation of their service life is based on empirical data and/or standardized testing procedures, e.g., ISO 16890. By applying standardized synthetic test dusts at constant reference humidity, these testing procedures do not reflect application-typical loading conditions. Based on a direct comparison with field data, the influence of temporary exposure to high relative humidity on differential pressure and particle deposit structure is investigated. The results indicate that simulating humidity variations of the ambient atmosphere during filter tests leads to particle deposits, which more accurately reflect the actual behavior during operation.

Hybrid power quality conditioner (HPQC) has been utilised in a co‐phase electrified railway system with the aim of improving power quality indices. A C‐type filter is designed as an auxiliary device alongside the HPQC for high‐order harmonics mitigation in this paper. Alternatively, the C‐type filter compensates a selected portion of load reactive power, while the HPQC compensates for the left required power. Furthermore, the HPQC mitigates grid side unbalance and other harmonics in a co‐phase supplied system simultaneously. In addition, a design procedure of LCL filters is proposed to suppress high‐order harmonic contents induced by the HPQC converters to achieve lower grid‐side total harmonic distortion (THD). Moreover, a flexible partial compensation (PC) method considering the C‐type filter effect on the HPQC performance is adapted to maintain the grid‐side power quality indices in an acceptable range. The C‐type filter and PC method provide VA rating reduction of the HPQC without applying any complication to the compensation control system. Finally, simulation and experimental results are presented to validate the feasibility and functionality of the proposed configuration.

In the conventional airborne telemetry system, the pre‐modulation filter with a multi‐pole active Bessel filter is preferred to use in Pulse Code Modulator (PCM)/FM transmission. In the existing system, it is not possible to change the cut‐off frequency for different data rates dynamically as required in the launch scenario of a long‐range aerospace vehicle. In general, aerospace vehicle has multiple propellant stages to travel a desired trajectory path. Each stage gets separated from the vehicle at different instances. Each stage measurement plan is defined and correspondingly the PCM format is generated with an optimum data rate. Hence, the telemetry system is required to transmit variable data rates at various instances of a long‐range aerospace vehicle from launch point to end point of a vehicle. This can be addressed by designing a dynamically tuneable pre‐modulation (DTPM) filter. Here, a suitable DTPM filter scheme is proposed to mitigate variable data rate transmission in the telemetry system. The scheme is analysed as per IRIG‐106 standard and simulated using MATLAB. The same has been modelled using VHDL and implemented targeting 28 nm technology Xilinx Zynq FPGA device.

The second edition of the book extends the scope of the first edition to the emerging topic of Dc Power Distribution Systems . Starting from the converter circuit analyses, small‐signal modeling and dynamic analyses, and control designs for standalone dc‐to‐dc converters, the book culminates with Four New Chapters about Dc Power Distribution Systems , covering the system stability, subsystem compatibility, line filter considerations, and system design/integration for predictable/programmable performance.

GaAs on Si grown via metalorganic chemical vapor deposition is demonstrated using various Si substrate thicknesses and three types of dislocation filter layers (DFLs). The bowing was used to measure wafer‐scale characteristics. The surface morphology and electron channeling contrast imaging (ECCI) were used to analyze the material quality of GaAs films. Only 3‐μm bowing was observed using the 725‐μm‐thick Si substrate. The bowing shows similar levels among the samples with DFLs, indicating that the Si substrate thickness mostly determines the bowing. According to the surface morphology and ECCI results, the compressive strained indium gallium arsenide/GaAs DFLs show an atomically flat surface with a root mean square value of 1.288 nm and minimum threading dislocation density (TDD) value of 2.4 × 107 cm−2. For lattice‐matched DFLs, the indium gallium phosphide/GaAs DFLs are more effective in reducing the TDD than aluminum gallium arsenide/GaAs DFLs. Finally, we found that the strained DFLs can block propagate TDD effectively. The strained DFLs on the 725‐μm‐thick Si substrate can be used for the large‐scale integration of GaAs on Si with less bowing and low TDD.

The Hodrick–Prescott (HP) filter is a commonly used tool in macroeconomics to obtain the HP filter trend of a macroeconomic variable. In macroeconomics, the difference between the original series and this trend is called the ‘cyclical component’. In this article, we derive the autocovariance function and the spectrum of the cyclical component of a series that consists of a constant, a linear time trend, a unit root process, and a weakly stationary process. We show that the autocovariance function of the cyclical component of such a series depends on (i) the autocovariance of the innovations of the unit root process; (ii) the autocovariance of the weakly stationary process and; (iii) a component of the weights of the HP filter that is important in the middle of a large sample. The result for the spectrum of the cyclical component matches with earlier results in the literature that were obtained by using an approximate approach. Lastly, we derive the cross-covariance function and the cross-spectrum of the cyclical components of two cointegrated series.

Newly germinated seedlings are vulnerable to biomass removal but usually have at least six months to grow before they are exposed to dry-season fires, a major disturbance in savannas. In contrast, plants are exposed to browsers from the time they germinate, making browsing potentially a very powerful bottleneck for establishing seedlings. Here we assess the resilience of seedlings of 10 savanna tree species to top-kill during the first 6 months of growth. Newly-germinated seeds from four dominant African genera from across the rainfall gradient were planted in a common garden experiment at the Wits Rural Facility and clipped at 1 cm when they were ~2, 3, 4, and 5 months old. Survival, growth, and key plant traits were monitored for the following 2.5 years. Seedlings from environments with high herbivory pressure survived top-kill at a younger age than those from low-herbivore environments, and more palatable genera had higher herbivore-tolerance. Most individuals that survived were able to recover lost biomass within 12 months, but the clipping treatment affected root mass fraction and branching patterns. Synthesis: The impact of early browsing as a demographic bottleneck can be predicted by integrating information on the probability of being browsed and the probability of surviving a browse event. Establishment limitation through early-browsing is an under-recognised constraint on savanna tree species distributions.

Here we report on initial efforts to evaluate enhanced darkfield microscopy (EDFM) and light scattering Vis-NIR hyperspectral imaging (HSI) as a rapid screening tool for the offline analysis of mixed cellulose ester (MCE) filter media used to collect airborne nanoparticulate from work environments. For this study, the materials of interest were nanoscale titanium dioxide (TiO2 ) and silicon dioxide (SiO2 ; silica), chosen for their frequent use in consumer products. TiO2 and SiO2 nanoscale particles (NPs) were collected on MCE filter media and were imaged and analyzed via EDFM-HSI. When visualized by EDFM, TiO2 and SiO2 NPs were readily apparent as bright spherical structures against a dark background. Moreover, TiO2 and SiO2 NPs were identified in hyperspectral images. EDFM-HSI images and data were compared to scanning transmission electron microscopy (STEM), a NIST-traceable technique for particle size analysis, and the current gold standard for offline analysis of filter media. As expected, STEM provided more accurate sizing and morphology data when compared to EDFM-HSI, but is not ideal for rapid screening of the presence of NPs of interest since it is a costly, low-throughput technique. In this study, we demonstrate the utility of EDFM-HSI in rapidly visualizing and identifying TiO2 and SiO2 NPs on MCE filters. This screening method may prove useful in expediting time-to-knowledge compared to electron microscopy. Future work will expand this evaluation to other industrially relevant NPs, other filter media types, and real-world filter samples from occupational exposure assessments.

Residence time distribution modeling of integrated perfusion to capture process can elucidate the impact of product quality excursions and filter fouling on monoclonal antibody production. In this case study, a glycosylation inhibitor and fluorescently labeled antibody are applied to the continuous process to study protein quality modulation, perfusion filter fouling, and unit operation hold times. The unit operations were modeled as continuous-stirred tank reactors and the residence time distribution of a small molecule glycan inhibitor and impact on glycosylation were characterized. A fluorescently labeled antibody was applied as a tracer molecule and confirmed the impact of packed cell volume and filter fouling. This study demonstrates how a biologics continuous process can be modeled and characterized through residence time distribution to ensure a robust, well-understood process.

Conventional signal processing techniques for fault detection are usually aimed at constant speed conditions. Nowadays, order tracking, especially tacho‐less order tracking is regarded as a valuable tool for extracting fault features under variable rotational speed conditions. Therefore, a teager energy operator (TEO)‐based modified Laplacian of Gaussian filter is proposed to enhance the fault detection behaviour of tacho‐less order tracking. This method consists of four steps: First, multi‐synchrosqueezing transform is employed to estimate and then extract the instantaneous rotation frequency of a shaft. Second, based on the extracted curve, the non‐stationary domain signal is converted into a quasi‐stationary domain by the re‐sampling technique. Third, the obtained quasi‐stationary domain signal is de‐noise by the novel method. Finally, fault characteristic orders are extracted via envelope order spectrum analysis method and the performance is significantly improved. The results of numerical simulation and experimental investigations are performed to validate the superiority of the novel method for fault extraction under variable rotational speed conditions.

To reject the disturbances of the nonminimum‐phase systems, the generalised dual‐filter disturbance observer is proposed. The conventional disturbance observer methods inevitably lead to nonminimum‐phase systems' instability. To stabilise the system, the forward plant and dual filters are introduced. The stability constraints are transferred to the dual filters. Based on any stable designs of the close‐loop controller, the dual filters can be easily designed. The simulations effectively verify that the disturbance rejection performances of the proposed method are triple those of the closed‐loop nonminimum‐phase system, and the original system's tracking capabilities and stability margins are few affected.

Polyethyleneimine-layered membrane with grafted heparin (oXiris) may improve filter life during continuous renal replacement therapy (CRRT) in addition to its immunoadsorptive capability, compared with that of conventional membrane. In this single center, prospective, open-label pilot study, we randomized critically ill patients with bleeding risk who underwent anticoagulation-free CRRT, to commence with oXiris or M150 filter with sequential crossover. We examined the filter life with each circuit and its effect on systemic coagulation parameters. We randomized 11 and nine patients to commence CRRT with oXiris and M150 respectively, with 19 oXiris and 20 M150 filter-circuits in all. Patient profiles in both arms were comparable for illness severity and comorbidities. Median filter lives for oXiris versus M150 circuits were 13 h versus 18 h (p = 0.10). Among 11 patients with paired crossover filters, filter lives for 14 oXiris-M150 circuit pairs were 13 h versus 16 h (p = 0.27), and corresponding transmembrane pressures increased to 111 mmHg versus 75 mmHg by 12 h (p = 0.02). Patients' coagulation parameters were comparable following both filter-circuits. CRRT with oXiris (vs. M150) was independently associated with shorter filter life, adjusted for prescribed dose, vascular access, and coagulopathy. Use of oXiris did not prolong filter life over conventional membrane with no evidence of systemic heparin exposure; significant membrane clogging is observed by 12 h with oXiris.