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This work, for the first time, presents an absorptive frequency-tunable substrate-integrated waveguide (SIW) filter. For the filter design, an absorptive bandpass filter prototype tailored to an SIW structure has been formulated. The proposed absorptive bandpass filter prototype is capable of having a return loss larger than 20 dB at all frequencies although it has a simple matching circuit. The filter prototype has been attained by comprehensive formula-based synthesis of a new matching circuit equivalent to an existing one. To validate our filter prototype, a second-order absorptive bandpass filter that can alter its center frequency has been designed, fabricated, and measured. This article demonstrates approaches to find physical dimensions by comparing each section of the filter structure with the corresponding part of the prototype. The fabricated absorptive bandpass filter has a compact structure by virtue of its simple matching section. The frequency-tunable SIW resonators allow our absorptive bandpass filter to adjust its center frequency from 1.76 to 2.69 GHz while having absorptive performance. The measured reflection of the filter centered at 2.50 GHz is smaller than -10 dB between 1.56 and 3.27 GHz (2.10:1). It is shown that theory, simulation results, and measured responses are in good agreement.

A low-power 113-dB SNR, -93-dB total harmonic distortion (THD)+N, digital input Δ Σ-based filter-less Class-D amplifier for wireless headphone applications is presented. This performance is achieved by the following architecture improvements: 1) variable-frequency-Δ Σ Class-D with digital feed-forward and switching-frequency reduction, 2) common-mode-stabilized power stage, 3) current digital-to-analog converter direct drive, and 4) rotational first-order dynamic-element-matching techniques. It operates on a single 1.8-V power supply with no external passive components except for a supply decoupling capacitor. The Class-D headphone amplifier achieves 82-mW non-clipping output power with 93% efficiency at a 16-Ω and 33-μH load condition. The complete system was fabricated in a 40-nm CMOS process and occupies 1.33-mm² die area.

This work presents the design of an additively manufactured W-band bandpass filter and a subtractively manufactured W-band diplexer in order to demonstrate the use of admittance inverter sequences for the ease of manufacture at millimetre-wave frequencies. Contrary to typical impedance inverters (E-plane and H-plane irises), the use of admittance inverters (E-plane and H-plane stubs) allow for larger dimensions to be specified and ultimately do not impede the general waveguide path. The proposed bandpass filter is designed with all E-plane stubs, while the diplexer is designed with one branch utilizing both E-plane and H-plane stubs as an arbitrary sequence, and the second branch utilizing all H-plane irises. The additively manufactured bandpass filter is fabricated using the most elementary level stereolithography (SLA) based methods, demonstrating that a hobbyist-type SLA printer and metallization method can procure exceptional results for millimeter-wave filter designs. The subtractively manufactured diplexer is fabricated using high-precision computer numerical control (CNC) milling in order to highlight the use of arbitrary inverter sequences in a more complex and robust design profile, while the dispersive transmission zeros that are caused by over-moding of the inverter stubs is utilized to demonstrate unique isolation characteristics in the upper W-band region. The design concepts, fabrication profiles, simulations and measurements which are presented in this work highlight a viable option for overcoming miniaturized dimensions in millimetre and sub-millimetre-wave applications.

This paper presents a compact and planar reconfigurable filtenna for application in Wireless systems. The filtenna is composed of a UWB circular antenna and a filter with two trapezoidal resonators. The filter is integrated on the antenna feed line and has a band-pass frequency response. The filtenna frequency response reconfiguration is achieved by changing the capacitance of a varactor diode, placed between filter resonators; the capacitance varies continuously from 1.32 pF to 4.09 pF according to an applied bias voltage. The varactor capacitance analog variation defines the filtenna frequency of operation, which can be varied from 2.2 GHz to 3.4 GHz with an average bandwidth of 200 MHz, while maintaining the radiation characteristics of the UWB antenna. Simulated and measured filtenna results are shown according to varactor diode bias, demonstrating multiband operation using a compact planar design.

This paper deals with the Bayesian state estimation of nonlinear stochastic dynamic systems. The stress is laid on the numerical solution to the Chapman-Kolmogorov equation, which governs the prediction step of the point-mass filter and predictor, using the convolution. A novel density-weighted convolution is proposed, which provides an accurate predictive probability density function even for models with small state noise, where the standard solution fails. Two implementations of the solution are proposed, theoretically analyzed, and evaluated in a numerical study.

This article discusses a rigorous and straightforward method to synthesize and design a transmission-line-based reflectionless bandstop filter with high performance in terms of reflectionless range. Our design strategy targets to allow a reflectionless bandstop filter to feature three distinguished advantages that are incomparable to others. First, the presented filter structure is capable of producing an exceptional broadband impedance matching performance. Second, it can be designed to have an extended upper passband. Third, an Nth-order filter has N coupling structures and each of them is used twice in design. Hence, it is required to design and tune only N coupling structures, whereas other design approaches use more than N distinct coupling structures. Although reflectionless filters having one of the aforementioned features have been reported, one exhibiting all the characteristics has never been reported to date. Fabricated filter examples fully validate the design theory.

INTRODUCTION: OMERACT uses an evidence-based framework known as the 'OMERACT Filter Instrument Selection Algorithm' (OFISA) to guide decisions in the assessment of outcome measurement instruments for inclusion in a core outcome set for interventional and observational clinical trials.METHODS: A group of OMERACT imaging and patient-centered outcome methodologists worked with imaging outcome groups to facilitate the selection of imaging outcome measurement instruments using the OFISA approach. The lessons learned from this work influenced the evolution to Filter 2.2 and necessitated changes to OMERACT's documentation and processes.RESULTS: OMERACT has revised documentation and processes to incorporate the evolution of instrument selection to Filter 2.2. These revisions include creation of a template for detailed definitions of the target domain which is a necessary first step for instrument selection, modifications to the Summary of Measurement Properties (SOMP) table to account for sources of variability, and development of standardized reporting tables for each measurement property.CONCLUSIONS: OMERACT Filter 2.2 represents additional modifications of the OMERACT guide for working groups in their rigorous assessment of measurement properties of instruments of various types, including imaging outcome measurement instruments. Enhanced reporting aims to increase the transparency of the evidence base leading to judgements for the endorsement of instruments in core outcome sets.

The short-circuit response of inverter-interfaced distributed generators (IIDGs) is not adequately represented in many conventional protection studies. This paper presents an in-depth analysis of IIDG behavior during grid faults and proposes a more accurate reduced-order parameterized short-circuit current (RPSC) model of inverters. Typical inverter components are thoroughly investigated to identify those that play dominant roles during faults. The paper shows that the current limiter is the dominant factor for the steady-state fault-current of inverter; while the inverter filter along with the severity of the voltage disturbance largely determine the initial transient spike of inverter fault current. The proposed model is low-order and can be used in large scale simulations. The parameters of the proposed RPSC model can be extracted from laboratory experiments without requiring proprietary manufacturer information. The proposed fault-current model is analogous to the well-known synchronous machine model that segregates the inverter fault current into subtransient, transient, and steady-state fault currents. Experimental and simulation tests are presented to validate the model.

In this paper a low-power and high-performance 2nd-order complex band-pass filter in trans-impedance amplifier (TIA) configuration is presented. Thanks to the adopted topology for the passive network and active-components exceeds current solutions exhibiting a gain as high as 121.5 dB $_Ω$ and 1.57 MHz of bandwidth centered around 1.33 MHz. The output noise is only 630 nV/√Hz. Furthermore, a new fully-differential class-AB operational trans-conductance amplifier (OTA) provides the required current to drive heavy ADC loads with very fast signals while an improved common-mode feedback circuit enables ultra low current without introducing stability and avoids start-up problems. The filter has been integrated in a 90-nm complementary metal oxide semiconductor (CMOS) technology. Despite the high performance and accuracy of the transfer function the power consumption is only 400 μA from a 1.2-V power supply.

In the permanent magnet synchronous motor speed regulation system, the dynamic performance of the conventional active disturbance rejection control (ADRC) system will be deteriorated by using a low bandwidth speed filter. To solve this problem, two ADRC controllers considering the speed measurement noise are proposed in this article. One proposed ADRC system is based on the extended state observer (ESO), the other proposed ADRC system is based on phase-locking loop observer (PLLO). In the proposed two ADRC systems, an integrator is employed as the speed filter so that the measured position can be directly used for observing the speed and disturbance without speed calculation. Meanwhile, by using an integrator as the speed filter, the dynamic performance of the proposed ESO-based ADRC system is not affected since it is independent of the speed filter, and the proposed PLLO-based ADRC system has a better rejection ability for the low-frequency disturbance. Experimental results validate the proposed methods. Ministry of Education (MOE) Accepted version This work was supported in part by the Academic Research Fund Tier 1 from Ministry of Education, Singapore, under Grant 04MNP000588C140, and in part by the Natural Science Foundation of China under Grant 51807080.

The accurate state of charge (SoC) estimator has great significance for ensuring the safety and reliability of Li-ion battery systems. However, the accurate SoC estimation for a series–parallel connected battery pack is a remaining challenge due to the strong inconsistency characteristic caused by cell open-circuit (COC) faults. Therefore, a novel fault-tolerant multimodule SoC estimation method for the series–parallel connected battery pack is proposed. An average module model is used to describe the performance of the battery pack. A bias correction model considering SoC, series resistance, and polarization characteristic inconsistency is developed to describe in-pack modules. A noise adaptive H ∞ filter-unscented H ∞ filter is employed to estimate SoC for the average module. The SoCs of in-pack modules are obtained by an optimized recursive least square method. A correlation coefficient-based method is developed to detect COC fault and isolate the fault module. Finally, several experiments on a 4s-3p battery pack are taken to evaluate and verify the real-time performance, stability, and accuracy of the proposed method. The result shows that both online and offline SoC estimation error is less than 1% for healthy modules, and it is less than 2.5% for the fault module in which one-third capacity is lost randomly.

With the rapid progress of the wireless communication technique and the fast growing of the radio frequency (RF) markets, the development of wideband surface acoustic wave (SAW) filter is intensely pursued in RF front-end platforms. In this study, a novel configuration of SAW device was proposed in 15°YX-LiNbO3 (300 ​nm)/SiO2 (600 ​nm)/Si heterostructure, where the series and shunt resonator innovatively adopt Cu electrodes of different thickness to suppress the unwanted Rayleigh mode efficiently. Series and shunt resonators with clean spectrum and high electromechanical coupling coefficients over 20% were experimentally achieved under the guidance of finite element method calculation. Based on the resonator results, a ladder-type SAW filter with a very large 3-dB fractional bandwidth near 30% was successfully designed and fabricated. The minimum insertion loss of device is as small as 1.1 ​dB while the in-band fluctuation is less than 0.3 ​dB. The unprecedented wideband property of SAW device indicates that the proposed configuration is expected to become one of the solutions of wideband filter in fifth-generation mobile communication, and possess great commercial application prospects.

The installment of $LC$ filter between the voltage source inverter and motor terminal can reduce the value of $dv$ / $dt$ considerably, and further mitigate the surge voltage stress on the motor windings during the long-distance transmission. However, the sophisticated controller needs to be designed to solve the additional resonance problems caused by the filter. Conventional active damping (AD) scheme mainly introduce the multiloop feedback based on the analysis in $s$ -domain or $z$ -domain, which is realized with limited bandwidth and high tuning complexity. In this article, the finite-control-set model predictive control (FCS-MPC) is adopted to realize the $q$ -axis current reference tracking for motor and suppress the filter resonance simultaneously. Different from the transfer-function-based AD scheme, the mechanism of resonance generation is revealed in the time-domain, where the cost function of FCS-MPC is designed to directly regulate the multivariable trajectory of the system. Therefore, the proposed FCS-MPC controller expresses the intuitive design principle, a simple structure, and fewer tuning parameters, which could be an alternative to the existing AD scheme. To reduce the number of sensors, the Kalman-filter based state estimation is used by considering the one-step delay of the control input. The cost function is further optimized to a simplified form that suits the implementation of the digital platform, and the lower computational burden is obtained. The experimental results prove that the proposed FCS-MPC scheme can ensure the motor-friendly waveform and overcome the resonance problem effectively. The robustness of the controller to parameter variations of the filter is also verified.

Hybrid orthogonal frequency division multiplexing-digital filter multiple access passive optical networks (OFDM-DFMA PONs) offer a cost-effective solution to the challenging requirements of next-generation optical access networks and 5G and beyond radio access networks. It is crucial to consider the impact of timing jitter in any ADC/DAC-based system, therefore this paper presents an in-depth investigation into the impacts of DAC/ADC timing jitter on the hybrid OFDM-DFMA PON's performance. We introduce improved accuracy white and coloured, DAC and ADC timing jitter models, applicable to any DSP-based transmission system. We prove that DAC and ADC timing jitter effects are virtually identical and investigate the effects of white/coloured timing jitter on upstream performance in hybrid OFDM-DFMA PONs and determine the associated jitter-induced optical power penalties. To mitigate against the timing jitter-induced performance degradations, a simple, but highly effective DSP-based technique is implemented which increases robustness against the timing jitter effects and significantly reduces timing jitter-induced optical power penalties. This consequently relaxes DAC/ADC sampling clock jitter requirements and so reduces implementation costs. White (coloured) timing jitter effects are shown to be independent of (dependent on) ONU operating frequency band and a trade-off between DAC and ADC jitter levels can be exploited to reduce ONU costs.

Purpose Inferior vena cava (IVC) filter tilt may lead to apex embedment and need for advanced retrieval techniques. This study assesses factors associated with filter tilt change over time and need for complex retrieval procedures. Materials and methods 252 consecutive patients underwent retrievable IVC filter placement and removal at a single academic institution over 58 months. 182 (72.2%) patients met inclusion criteria. IVC filters included 168 (92.3%) Gunther Tulip and 14 (7.7%) Option filters. The primary outcome was medial-to-lateral IVC filter tilt change between placement and retrieval. Secondary outcomes included advanced retrieval technique use and multiple retrieval attempts. Independent variables included demographics, IVC diameter, filter hook position relative to the renal veins, and dwell time. Associations were determined using student's t-tests, ANOVA, and linear and logistic regressions. Results Mean IVC diameter at placement was 19.2 ± 3.3 mm. Mean filter tilts at placement and retrieval were 6.1 ± 4.9° and 5.2 ± 5.0°, respectively. Mean tilt change was 5.0 ± 5.0°. Larger IVC diameter was associated with greater filter tilt change (p = 0.0004). While IVC diameter did not independently predict retrieval difficulty, greater tilt change and prolonged dwell time were associated with increased advanced retrieval technique use (p = 0.01 and 0.002, respectively). Results were unchanged in a subgroup analysis of patients treated with Gunther Tulip filters. Conclusion Larger IVC diameter predicts increased filter tilt change, which in turn is associated with challenging retrievals. Attention to IVC diameter during filter placement may anticipate tilt-related complications.

The emergence of large-scale dynamic sets in networked and distributed applications attaches stringent requirements to approximate set representation. The existing data structures (including Bloom filter, Cuckoo filter, and their variants) preserve a tight dependency between the cells or buckets for an element and the lengths of the filters. This dependency, however, degrades the capacity elasticity, space efficiency and design flexibility of these data structures when representing dynamic sets. In this paper, we first propose the Index-Independent Cuckoo filter (I2CF), a probabilistic data structure that decouples the dependency between the length of the filter and the indices of buckets which store the information of elements. At its core, an I2CF maintains a consistent hash ring to assign buckets to the elements and generalizes the Cuckoo filter by providing optional k candidate buckets to each element. By adding and removing buckets adaptively, I2CF supports the bucket-level capacity alteration for dynamic set representation. Moreover, in case of a sudden increase or decrease of set cardinality, we further organize multiple I2CFs as a Consistent Cuckoo filter (CCF) to provide the filter-level capacity elasticity. By adding untapped I2CFs or merging under-utilized I2CFs, CCF is capable of resizing its capacity instantly. The trace-driven experiments indicate that CCF outperforms its alternatives and realizes our design rationales for dynamic set representation simultaneously, at the cost of a little higher complexity.

The gravel granular filter has been widely used to eliminate the strong shock waves induced by deliberated and occasional explosions. The modelling of shock wave propagation and attenuation in the gravel granular filter is still not well resolved and is a topic of current research. In this study, a new three-dimensional mesoscopic model of gravel granular filter is presented. This involves establishing the geometric model of three-dimensional gravel particles with the consideration of random shape based on the Voronoi algorithm, then generating the corresponding FE mesh based on the mapping grid algorithm and finally precisely controlling the porosity by applying a given displacement load. The three-dimensional mesoscopic model is then validated by numerically simulating two field tests on shock wave propagation and attenuation in a gravel granular filter. Detailed analysis of numerical simulations demonstrates that the drag force between gaseous phase and solid filter and the multiple complex reflection and diffraction between the particles are the main causes of the attenuation of shock wave with low amplitude. Finally, parametric study on the five dominant characteristics of filter, i.e., the particle shape, filter porosity, filter length, particle size and particle wave impedance are conducted. It is found that the particle shape, porosity, and wave impedance of filter have a strong influence on the capability of shock wave attenuation, and the filter length has limited influence beyond a critical optimal length, while the particle size has negligible effect.

Considering L as a complete residuated lattice, some further investigations on L-filter spaces are made. Firstly, it is shown that the category L-Fil of L-filter spaces is monoidal closed. Secondly, it is proved that the categories of L-Cauchy spaces and L-semi-Cauchy spaces are both bireective subcategories of L-Fil. Finally, the concept of filter-determined L-semiuniform convergence spaces is proposed and the resulting category is shown to be isomorphic to L-Fil, which can be embedded in the category of L-semiuniform convergence spaces as a bicoreective subcategory. Moreover, it is proved that L-Fil can be embedded in the category of L-semiuniform convergence spaces as a bireective subcategory whenever L is a completely distributive lattice.

This is a knowledge contribution to the unsatisfactory biodegradation problem, when biotrickling filters are purifying mixed paint solvents. A biotrickling filter manufacturer reported low biodegradation rates during the purification of a hydrocarbon pollutant mix from an industrial paint spraying floor. From a gas chromatograph/mass spectrometer analysis both hydrophilic and hydrophobic solvents were found in the polluted air. It is known that biodegradation is retarded, if the pollutant does not transfer from gas to liquid into the biofilm and it was therefore suspected that hydrophobic pollutants do not sufficiently migrate into the water/biofilm. To test this hypothesis, pure, rather than mixed pollutants, were injected into the abiotic biotrickling filter. When hydrophobic paint solvent (xylene) was sprayed into the biotrickling filter, the solvent load at the outlet of the filter was almost as high as at the inlet. But when pure, hydrophilic paint solvent (PGME) was sprayed into the abiotic biotrickling filter, the solvent load measured at the outlet of the filter was zero, indicating complete dissolution into the circulation water. Carbon/solvent loads at the filter outlet and inlet were measured with a portable flame ionization detector instrument. The experiment confirms that the hydrophobic solvent does not migrate into the liquid phase. This poor mass transfer of hydrophobic solvents is likely to be the reason for the low biodegradation rate. The result is highly relevant to the paint spraying industry and manufacturers of exhaust gas treatment equipment alike, who spend millions in non-sustainable incineration of exhaust gases.

In this paper, we have focused to improve the performance of a speech-based uni-modal depression detection system, which is non-invasive, involves low cost and computation time in comparison to multi-modal systems. The performance of a decision system mainly depends on the choice of feature selection method and the classifier. We have investigated the combination of four well-known multivariate filter methods (minimum Redundancy Maximum Relevance, Scatter Ratio, Mahalanobis Distance, Fast Correlation Based feature selection) and four well-known classifiers (k-Nearest Neighbour, Linear Discriminant classifier, Decision Tree, Support Vector Machine) to obtain a minimal set of relevant and non-redundant features to improve the performance. This will speed up the acquisition of features from speech and build the decision system with low cost and complexity. Experimental results on the high and low-level features of recent work on the DAICWOZ dataset demonstrate the superior performance of the combination of Scatter Ratio and LDC as well as that of Mahalanobis Distance and LDC, in comparison to other combinations and existing speech-based depression results, for both gender independent and gender-based studies. Further, these combinations have also outperformed a few multimodal systems. It was noted that low-level features are more discriminatory and provide a better f1 score.

Filters are important pieces of equipment to ensure the normal operation of micro-irrigation systems, and the head loss is a key indicator to evaluate their hydraulic performances. To reduce the head loss and energy consumption, a new type of filter for treating surface water – the pre-pump micro-pressure filter was proposed. The pre-pump micro-pressure filter was studied, and physical model tests on the flow rate, water separator type, and filter screen area were conducted under clean water conditions. Statistical and dimensional analysis methods were used to analyze the test results. Our results showed that the order of the factors affecting the head loss of the filter was flow rate > water separator type > filter screen area. The various water separator types showed no significant differences in terms of head loss, while the different flow rates showed significant differences. A head loss prediction model was constructed, and the coefficient of determination R2 reached 0.987. Our results can provide technical support for new filter development and enrich the theory of micro-pressure filtration.

This paper presents a new mutually coupled circuit (MCC) based on voltage differencing current conveyor (VDCC). The proposed MCC has been designed using the Gorski-Popiel technique. The proposed circuit consists of two VDCCs as active elements, three resistors, and two grounded capacitors as passive elements. The primary and secondary self-inductances and the mutual inductance can be controlled independently and can be adjusted electronically by the bias current of the VDCCs. There is only one matching condition for satisfying symmetrical coupling. Time and frequency-domain analyses have been performed with the LTspice program to verify the theoretical analyses. A double-tuned band-pass filter application is given to show the functionality of the proposed MCC.

El presente trabajo de investigación tiene como objetivo de implementar un Módulo de Práctica de Filtros Digitales FIR para la Carrera Teleinformática de la Universidad de Guayaquil. Se utilizó el método bibliográfico para determinar que el método matemático de ventana es el más adecuado para el diseño de los filtros digitales FIR porque permitió usar hardware programable para implementar los diferentes tipos de filtros digitales, para la implementación del módulo se usó el método experimental y por último, se utilizó el método indagación para determinar la usabilidad del módulo a través de encuesta que se aplicó a los 13 estudiantes de octavo semestre que estaban registrado en la materia de Simulación de Sistema de la Carrera Ingeniería de Teleinformática de la Universidad de Guayaquil en el período académico Ciclo 2019 – 2020 CII. Se realizó una comparación de la respuesta de salida de cada filtro implementado experimentalmente del módulo con la respuesta de salida simulada observándose un mínimo error entre ellos y que la respuesta de salida experimental tiene una mayor ganancia, también se monitoreo el tiempo de ejecución de la práctica obteniéndose como promedio total 84,75 minutos de la implementación y por último se obtuvo que más del 90% de los encuestados indicó que el módulo era un sistema útil, intuitivo, amigable, eficiente y fiable. Se concluye que la implementación del Módulo tiene una respuesta excelente de salida experimental, optimiza tiempo de práctica y que tuvo una buena aceptación de los estudiantes.

In this paper, Sensorless Permanent Magnet Synchronous Motor (PMSM) using Extended Kalman Filter (EKF) is presented. The previous PMSM drive uses a sensor to measure the motor’s speed. Then the idea is to replace the sensor by using sensorless drives based on the observer. For the conventional observer, it’s only good for low current and low-speed applications. Moreover, it is hard to detect the phase voltage due to the non-existence of neutral wire. Therefore, this project proposes sensorless control using an EKF. This method provides an optional estimation algorithm for the non-linear system that can produce a fast and accurate estimation of state variables. The accurate estimation will reduce the noise and ripple of the system. Additionally, the EKF do not require the information of mechanical parameters and the initial position of the rotor, making the construction is easy and simple. In this paper, the fundamental of the EKF algorithm is explained and the simulation results for different speeds and loads are presented. The noise reduction test is also conducted to measure the flux current with and without the filter. The simulation study is achieved using MATLAB/Simulink to verify the effectiveness of the proposed method. The results of the simulation show that the sensorless PMSM drives using EKF have lower overshoot and faster rise time during start-up conditions and have lower undershoot during the loaded condition. It also can be concluded that the proposed sensorless PMSM drive using EKF has good speed control accuracy and can reduce the current noise.

This article suggests an open-ended coplanar waveguide band-pass filter using stepped-impedance resonators (SIR) and complementary split-ring resonators (CSRR) that operates at a wider bandwidth with higher band selectivity at 4G—LTE applications. The filter described here is collimated to work in the frequency range of 2.23–4.2 GHz. SIR is used to provide improved selectivity at 2.6 GHz and 3.5 GHz with a return loss of − 30 dB and an insertion loss of − 0.2 dB. Similarly, including CSRR in the design aided in attaining broader bandwidth by ensuring a low ripple value across the bandwidth. The fractional bandwidth of 61.3 percent and a 2 GHz broad band coverage is accomplished with a small footprint of (16 × 16 × 0.8) mm3. The decreased dimensions of the filter result in a group delay of 0.5 ns for maximum filter performance. By loading CSRR into the structure, it established double negative property in the simulated frequency range of interest. A vector network analyzer is used to evaluate system characteristics such as operational bandwidth, return loss, and insertion loss (VNA). The filter’s electrical size (0.19 × 0.19) $${\uplambda }_{\mathrm{g}}$$ compactness substantiates its application in 4G—LTE—WLAN/WiMaX standards.

This article deals with automatic generation control (AGC) of a three-area power system having five diversified sources of generation like thermal unit, hydro unit, wind unit, diesel unit and a gas unit are interconnected together. Area-1 of the power system consists of a thermal, a hydro and a wind unit, area-2 has a thermal, a hydro and a diesel unit and area-3 consists of a thermal, a hydro and a gas unit. To make system more realistic different nonlinear components like governor dead band (GDB), generation rate constraint (GRC), boiler dynamics and communication delay are taken into account. A novel two-degree of freedom fractional order PID with derivative filter and fractional order PD with derivative filter (2-DOF-FOPIDN-FOPDN) cascaded control strategy is adopted to improve the dynamic performance of the power system. The results obtained with the proposed cascaded controller are compared with that of PID, FOPID and 2-DOF-PIDN-PDN cascaded controller to prove its superiority. To enumerate the gains of different controllers optimally, a recently developed bio-inspired optimisation algorithm named selfish herd optimisation (SHO) is capitalised. Further, the work is extended by taking a two-area hydro-thermal system to compare the result of the SHO tuned PID controller with that of modern hybrid firefly algorithm-pattern search (hFA-PS) technique. Transient analysis is carried out by applying a sudden load disturbance of 0.01 p.u in area-1 and the robustness of the controller is examined by varying both system parameters and applying a randomly varying load in area-1. From the investigation it is concluded that the 2-DOF-FOPIDN-FOPDN controller gives a flawless and a distinct performance.

Multipliers are the most demanding component of any filter. They not only dominate most of the chip area but also contribute to most of the computational delay. An efficient realization of filter thus requires optimization of the multipliers. In this paper, a high performance block reconfigurable finite impulse response filter structure is presented. Block-based realization improves the overall throughput of the structure. A novel partial-product-based structure is proposed for Multiply and Accumulation operation, instead of traditional multipliers-based structure. Pipelining and parallelism in the structure improves the throughput of the design. The reuse of the partial products reduces the number of adders and increases the speed, thereby reducing the area-delay product (ADP) and energy-per output (EPO), in comparison with the earlier reported structures. The comparative analysis is done with the help of ASIC synthesis results and the results show that the proposed architecture for filter order 16 and block input 8requires 28.91% less ADP and 25.72% less EPO than the earlier reported architecture.

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.

A positioning system estimates the position and orientation of a vehicle. Autonomous driving systems plan paths and control the vehicle based on the information from the positioning system. Recently, methods of estimating the position in urban areas have been actively studied. In U-turn sections, which are common in urban areas, vehicles perform a rotation to reverse the direction of travel. Through these sections, drivers can reduce the travel distance and save time but with a high risk of an accident. Despite there being a need for the development of autonomous driving schemes for U-turn sections, the existing research is limited. This study proposes an interacting multiple model (IMM) filter-based position estimation algorithm for urban U-turn sections. To reflect the dynamic characteristics of a vehicle during U-turn maneuvers, a multiple vehicle model was used. This model includes kinematic and dynamic vehicle models. The state estimates of the vehicle model and gyroscope are combined using an IMM filter. The position estimation algorithm developed in this study is verified via experiments. The experimental results indicate that, during urban U-turn maneuvers, the position estimation accuracy of the IMM filter-based algorithm is improved than that of the single vehicle model.

This paper aims to improve the rapidity and accuracy of the State of Health (SOH) assessment for lithium-ion battery. By integrating the Unscented Kalman Filter (UKF) and Improved Unscented Particle Filter (IUPF) algorithm, SOH can be effectively evaluated. The UKF algorithm is used to estimate the state of charge (SOC), the IUPF algorithm is employed to identify the ohmic internal resistance. The novelty of the proposed strategy relies on the 4-dimensional IUPF filter that is split into a 3-dimensional UKF filter and a 1-dimensional IUPF filter. Experimental results demonstrate that more accuracy and a faster rate of SOH estimation can be achieved via the UKFIUPF algorithm compared to the IUPF approach.

Aerosolization of SARS-CoV-2 by COVID-19 patients can put healthcare workers and susceptible individuals at risk of infection. Air sampling for SARS-CoV-2 has been conducted in healthcare settings, but methods vary widely and there is need for improvement. The objective of this study was to evaluate the feasibility of using a high-volume filter sampler, BioCapture z720, to detect SARS-CoV-2 in COVID-19 patient rooms in a medical intensive care unit, a dedicated COVID-19 ward, and at nurses’ stations. In some locations, the BioSpot-VIVAS, known for high efficiency in the collection of virus-containing bioaerosols, was also operated. The samples were processed for SARS-CoV-2 RNA with multi-plex nested polymerase chain reaction. One of 28 samples collected with the high-volume filter sampler was positive for SARS-CoV-2; all 6 samples collected with BioSpot-VIVAS were negative for SARS-CoV-2. The high-volume filter sampler was more portable and less intrusive in patient rooms than the BioSpot-VIVAS, but limits of detection remain unknown for this device. This study will inform future work to evaluate the reliability of these types of instruments and inform best practices for their use in healthcare environments for SARS-CoV-2 air sampling.

Convolutional neural network (CNN) have been widely used in speech recognition, object detection and image recognition. In the process of inference, data access operations consume more energy than calculations. Therefore, optimizing the dataflow from external storage to the on-chip processing unit is an effective method to reduce the power consumption. The state-of-the-art row stationary dataflow maximizes the data reusing to reduce the number of data movement and thus reducing the power consumption of the system. However, it has the problems of low processing unit utilization and poor scalability. In this letter, we propose an enhance row stationary (ERS) dataflow. ERS dataflow maps the data of each channel of the three-dimensional filter and input feature map (ifmap) into a column of processing units by changing the mapping of data. The processing array operates multiple filters in parallel, which effectively improves the utilization of computing resources. Within each processing unit, one row of filter data and one row of ifmap data are processed at a time, and the filter row data and ifmap row data are reused in multiple convolution operations. In addition, a configurable sliding window model is proposed to solve the problem that the existing dataflow cannot handle the calculation array width smaller than the filter width. Simulation results show that for AlexNet and VGG16, the execution speed of ERS dataflow is improved by about 60% compared with row stationary dataflow, and the hardware resource utilization is improved by about 30%. For the MobileNet V1, the execution speed of ERS dataflow is improved by about 4% compared with the row stationary dataflow.

Background: Informative gene selection is an essential step in performing tumor classification. However, it is difficult to select informative genes related to tumors from large-scale gene expression profiles because of their characteristics, such as high dimensionality, relatively small samples, and class imbalance, and some genes are superfluous and irrelevant. Objective: Many researchers analyze and process gene expression data to obtain classified gene subsets by using machine learning methods. However, the gene expression profiles of tumors often have massive computational challenges. In addition, when improving feature importance and classification accuracy, cost estimation is often ignored in traditional feature selection algorithms, which makes tumor classification more difficult. Methods: In this study, a novel informative gene selection method based on cost-sensitive fast correlation- based filter (CS-FCBF) feature selection is proposed. Results: First, the symmetric uncertainty index is used to evaluate the correlation between informativeFirst, the symmetric uncertainty index is used to evaluate the correlation between informative genes and class labels, then a large number of irrelevant and redundant genes are quickly filtered according to importance. Thereby, a candidate gene subset is generated. Second, costsensitive learning, which introduces the misclassification cost matrix and support vector machine attribute evaluation, is used to obtain the top-ranked gene subset with minimum misclassification loss. Finally, the candidate gene subset is optimized. genes and class labels, then a large number of irrelevant and redundant genes are quickly filtered according to importance. Thereby, a candidate gene subset is generated. Second, costsensitive learning, which introduces the misclassification cost matrix and support vector machine attribute evaluation, is used to obtain the top-ranked gene subset with minimum misclassification loss. Finally, the candidate gene subset is optimized. Conclusion: This experiment was verified in eight independent tumor datasets. By comparing and analyzing CS-FCBF with another three hybrids of typical gene selection algorithms combined with cost-sensitive learning, we found that the method proposed in this study has a better classification performance with fewer selected genes, which might provide guidance in tumor diagnosis and research.

Deconvolution mainly improves the resolution of seismic data by compressing seismic wavelets, which is of great significance in high-resolution processing of seismic data. Prediction-error filtering/least-square inverse filtering is widely used in seismic deconvolution and usually assumes that seismic data is stationary. Affected by factors such as earth filtering, actual seismic wavelets are time- and space-varying. Adaptive prediction-error filters are designed to effectively characterise the nonstationarity of seismic data by using iterative methods, however, it leads to problems such as slow calculation speed and high memory cost when dealing with large-scale data. We have proposed an adaptive deconvolution method based on a streaming prediction-error filter. Instead of using slow iterations, mathematical underdetermined problems with the new local smoothness constraints are analytically solved to predict time-varying seismic wavelets. To avoid the discontinuity of deconvolution results along the space axis, both time and space constraints are used to implement multichannel adaptive deconvolution. Meanwhile, we define the parameter of the time-varying prediction step that keeps the relative amplitude relationship among different reflections. The new deconvolution improves the resolution along the time direction while reducing the computational costs by a streaming computation, which is suitable for handling nonstationary large-scale data. Synthetic model and field data tests show that the proposed method can effectively improve the resolution of nonstationary seismic data, while maintaining the lateral continuity of seismic events. Furthermore, the relative amplitude relationship of different reflections is reasonably preserved.

This paper intends to provide a three-level CUK converter-based on-board electrical vehicle battery charger with improved power quality features. The proposed configuration includes a diode bridge rectifier followed by a DC–DC converter suitable for the universal input voltage variations (85–265 V). It offers reduced voltage stress across the switches, reduced filter size, high efficiency, and improved dynamic response. A feed-forward control scheme is implemented for the proper functioning of the proposed converter under constant current (CC) and constant voltage (CV) modes of operation. In this paper, the mathematical modeling, operational details, and components design of the PFC converter are analyzed in continuous current mode. The simulation study on a 3.2 kW, 400 V proposed converter is carried out with MATLAB Simulink toolbox, and a real-time implementation of the same specifications of the proposed system is developed to verify the simulation study. The steady-state and dynamic behavior of the converter is investigated for power quality features like total harmonics distortion and input power factor with resistive and battery loads. The onboard charger exhibits satisfactory operation in CC and CV modes to a wide range of supply voltage variations.

This primary aim of this philosopher paper investigates the efficacy of the noise dissolving algorithm hinge on TTSD (Triple Threshold Statistical Detection) filter that has been originated since 2018 is one of the highest efficacy for dissolving RIIN (Random-Intensity Impulse Noise), exclusively at dense distribution. As a results, there are three essential contributions: the exhaustive explanation of the TTSD filter algorithm and its computation examples, the calculation simulation of noise apprehension correctness and overall comparative simulation of noise dissolving effectiveness. For TTSD filter, three malleable offsets that are the complementary requirement are employed in the TTSD filter that can adequately resolve the limitation of the antecedent noise dissolving algorithms. The first malleable offset is calculated for determining the noise characteristic of all elements by using the mathematical verification. Next, the second malleable offset is calculated for determining the another noise characteristic by using the normal distribution mathematical verification (the average value and standard deviation value). Later, the third malleable offset is calculated for determining the another noise characteristic by using the quartile mathematical verification (median value). In the simulation inquisition, the bountiful standard portraits that are desecrated by RIIN (Random Intensity Impulse Noise) with many dense distributions are experimented by noise dissolving algorithm hinge on TTSD in both noise segregation and noise dissolving perspective.

Las redes sociales permitieron que las luchas de los movimientos sociales fueran globales, accesibles e interconectadas. Instagram permite la circulación de las miradas sobre el mundo a través de imágenes, fotografías y videos y la participación de sus usuarios/as en la creación de un discurso visual. Este artículo pretende describir la incorporación del filtro como pañuelo verde y el uso del color emblemático de la Campaña Nacional por el aborto en Argentina en publicaciones a modo de ejemplo desde una mirada multimodal que realizaron en Instagram en sus cuentas colectivos feministas asociados como @abortolegalmza entre 2018 y 2019. El uso del pañuelo verde como filtro y el empleo de los colores emblemáticos posiblemente crearon una marca que permitió el compromiso de jóvenes y adolescentes con los ejes de la Campaña. Así, lo visual en las redes sociales fue el mensaje y el medio por el cual los colectivos feministas en Argentina (entre el 2018 y 2019 y hasta la actualidad) propusieron nuevas prácticas discursivas.

Impulse and Gaussian are the two most common types of noise that affect digital images due to imperfections in the imaging process, compression, storage and communication. The conventional filtering approaches, however, reduce the image quality in terms of sharpness and resolution while suppressing the effects of noise. In this work, a machine learning-based filtering structure has been proposed preserves the image quality while effectively removing the noise. Specifically, a support vector machine classifier is employed to detect the type of noise affecting each pixel to select an appropriate filter. The choice of filters includes Median and Bilateral filters of different kernel sizes. The classifier is trained using example images with known noise parameters. The proposed filtering structure has been shown to perform better than the conventional approaches in terms of image quality metrics. Moreover, the design has been implemented as a hardware accelerator on an FPGA device using high-level synthesis tools.

High failure rate caused by distributed driving and the model uncertainty of the four-wheel independent control electric vehicle (FWI-EV) bring motion-state-identified challenges. For solving the identified problem and achieving accurate motion states of FWI-EV, this paper designs an innovative motion state observer based on dual strong tracking filter (DSTF), which consists of vehicle and driving identification layers. The strong tracking filter (STF) with time-varying fading factor is firstly introduced in driving identification layer to rapidly and accurately identify the driving torque mutation of driving system. The driving torque mutation is considered in the vehicle identification layer by data sharing between the two identification layers. The vehicle motion states fluctuated by driving torque mutation are accurately identified by vehicle identification layer based STF. The effectiveness of the design method has been validated by simulations.

Summary In this article we develop a method based on model-X knockoffs to find conditional associations that are consistent across environments, while controlling the false discovery rate. The motivation for this problem is that large datasets may contain numerous associations that are statistically significant and yet misleading, as they are induced by confounders or sampling imperfections. However, associations replicated under different conditions may be more interesting. In fact, sometimes consistency provably leads to valid causal inferences even if conditional associations do not. Although the proposed method is widely applicable, in this paper we highlight its relevance to genome-wide association studies, in which robustness across populations with diverse ancestries mitigates confounding due to unmeasured variants. The effectiveness of this approach is demonstrated by simulations and applications to UK Biobank data.

International audience; This letter proposes to apply the Kalman-like observer paradigm to general nonlinear systems by linearization along the estimated trajectory, similarly to an Extended Kalman Filter. The main difference is that the quadratic Riccati equation is replaced by a linear Lyapunov equation which can be solved and explicitly related to a determinability Gramian. This allows to show by Lyapunov analysis and without any ad-hoc assumption on the Riccati solution, that the resulting observer, called Extended Kalman-like Filter, can be made semi-globally convergent if the input is actively used to a) stabilize the (unknown) true trajectory, b) sufficiently excite the determinability of the linearized systems along the (known) estimated trajectory. A class of systems where this compromise can be reached is provided.