Filter Concept Research Articles

Filter Theory in Pre-Ordered Residuated Systems Using Intuitionistic Fuzzy Points

Using the notion of intuitionistic fuzzy points, the concept of intuitionistic fuzzy filters and [Formula: see text]-intuitionistic fuzzy filters in pre-ordered residuated systems are introduced, and several related properties are investigated. Characterizations of intuitionistic fuzzy filters and [Formula: see text]-intuitionistic fuzzy filters are studied. By forming sub-structures called intuitionistic level set, intuitionistic [Formula: see text]-set, intuitionistic [Formula: see text]-set, and [Formula: see text]-set, the conditions under which they can be filters will be tracked.

Dynamic state awareness for distribution network based on robust adaptive cubature kalman filter

With the rapid development of the economy and society, the demand for power quality is constantly increasing. As a crucial part of grid situational awareness, distribution network state estimation plays a vital role in providing critical data support for other advanced applications, which is significant for ensuring the safe and reliable operation of the distribution network. Therefore, this paper proposes a dynamic state awareness method for distribution networks based on the robust adaptive cubature Kalman filter (RACKF). The proposed solution, grounded on the core computational concept of the cubature Kalman filter (CKF), constructs a robust noise statistical estimator (NSE) composed of a biased NSE and an unbiased NSE to adapt to the unknown and time-varying process noise parameters in the dynamic state estimation process. The proposed solution can ensure that the calculated process noise parameters always meet the constraints and guarantee the robustness of the algorithm. In addition, an estimation strategy for the fusion of multi-time scale measurement data is developed according to the RACKF-based dynamic state estimation features in order to realize system state corrections and updates. The results of simulation experiments and comparisons with traditional CKF methods demonstrate the accuracy and superiority of the proposed solution.

Switchable SAW Resonators and Ladder Filters Composed of Interdigitated Combs.

This work presents the development of switchable surface acoustic wave (SAW) resonators fabricated on a LiNbO3 substrate, which uses the electrical Bragg bandgap concept to control the resonance frequency. The modification of the electrical condition of electrode arrays shifts their bandgap center frequency, which in turn changes the effective cavity length and resonance frequency of the resonator. This method uses the electrodes already present in SAW devices, thus reducing the complexity of potentially tunable SAW components. In this article, the electrodes that make up the cavity mirrors are connected into interdigitated comb pairs (IDCPs), reducing the necessary number of switches for operation. Finite-element method (FEM) simulations are used to analyze resonator operation and design difficulties are discussed. Frozen (with no possibility of switching) and switchable versions of a chosen resonator structure are fabricated to experimentally showcase resonator operation. It is found that it is possible to design switchable SAW resonators, which require a single switch and present a relative frequency jump of around 2.3%. Finally, frozen single-cell and four-cell ladder filters are fabricated as a proof of concept of a switchable SAW filter.

OS FUNDAMENTOS DA PRESUNÇÃO DE RELEVÂNCIA E TRANSCENDÊNCIA PARA O RECURSO ESPECIAL EM AÇÕES DE IMPROBIDADE ADMINISTRATIVA E A EFETIVIDADE DOS DIREITOS FUNDAMENTAIS

After the promulgation of Constitutional Amendment No. 125/2022, which introduced the relevance filter for the special appeal, it started a debate regarding the concept and scope of this institute, especially when considering the hypotheses of presumption of transcendence inserted in the constitutional text itself. In this research, we seek to address the concept of the relevance filter, focusing on a specific presumption hypothesis addressed in the constitutional text: the presumption of relevance in administrative improbity actions. In this area, using the method of bibliographic and documentary review and an interdisciplinary approach, the aim is, then, to justify the presumption of relevance in this specific hypothesis, proposing the recognition, also, of a presumption of transcendence. In this way, an alternative is proposed to support the possibility of setting precedents of a binding nature in administrative improbity actions, as a general rule, as a way of giving greater effectiveness to a liability regime with outstanding importance in the legal system, aiming to achieve fundamental rights.

Design of highly efficient filtering power amplifier with a wideband response for sub-6 GHz 5G applications

This paper presents the design of a filtering power amplifier (PA) with extra-high power-efficiency and wide bandwidth. To accomplish this, a novel approach is adopted by utilizing a wideband bandpass filter (BPF) as the output matching network (OMN) for the PA. The BPF compromises two paths, where each path consisting of two identical coupled lines that are interconnected to form a ring structure. The suggested configuration eliminates the need for a conventional OMN by integrating the input port of the filter with the drain node of the transistor, resulting in reduced size and losses and improved amplifier performance. The filter concept is illustrated using coupling matrix synthesis. A proof-of-concept filtering PA has been designed using a commercially available 10 W GaN HEMT. This amplifier was designed to operate in the frequency range of 3.0–5.0 GHz, yielding a fractional bandwidth of 50 %. According to achieved results, the drain efficiency and output power are 43.8–70.5 % and 40.2–41.8 dBm, respectively. As a result, the suggested filtering PA demonstrates significant performance in terms of filter bandwidth response and power amplification. Additionally, the proposed filtering PA has a broad operational bandwidth of 3.0–5.0 GHz, which covers the 5G New Radio (NR) n77 (3.3–4.2 GHz), n78 (3.3–3.8 GHz), and n79 (4.4–5.0 GHz) frequency bands.

Implementation of Shunt Active Power Filter Using DSP Controller Based on Synchronous Reference Frame for Harmonic Mitigation

This research paper introduces the concept of a shunt active power filter (SAPF) that leverages synchronous-reference-frame (SRF) theory to mitigate harmonics in the power system. The SAPF works by injecting a compensating current at the point of common coupling (PCC) to counteract the harmonics in the line and restore sinusoidal current waveforms. It employs a three-phase current-controlled voltage source inverter (VSI) with a DC link capacitor for active filtering. An SRF algorithm is designed for a low-voltage laboratory prototype utilizing the TMS320F28335 Digital Signal Processor (DSP). The experimental findings affirm that the control strategy effectively aligns with the recommended harmonic standard limits of IEEE 519-1992.

Cost-benefit analysis for SHM systems based on minimum detectable parameter change

Value of information (VoI) analysis can be used to assess the benefit of monitoring the health of infrastructure such as bridges and waterway locks. Such information supports decision-making processes, guiding operators towards the best actions for the infrastructure. In recent studies, VoI analysis is integrated with the modeling of the temporal evolution of structural conditions, so that the value of Structural Health Monitoring (VoSHM) can be assessed over the life cycle of the infrastructure. However, none of these studies considers the ability of the measurement system to detect small changes and its impact on the assessment of the VoI. This paper presents an approach to VoI assessment based on the concept of minimum change detectability and Bayesian linear filters. By exploiting a feature of the Kalman filter whereby posterior covariance is independent of observations, it is possible to predict the minimum shift in the mean value of a structural parameter for which its posterior density function would exceed a user-defined safety threshold. By constructing the decision tree and considering the cost of monitoring and maintenance, the value of detecting smaller changes can be estimated, which is the value of early change detection and performing preventive maintenance. As a proof of concept, this approach is applied to assess the VoSHM for a navigation lock built with precast reinforced concrete elements, where the steel bars in the chamber are damaged by fatigue and corrosion. The VoSHM is compared with the VoI associated to other Non Destructive Tests. The paper then discusses the implications of applying Bayesian linear filters in SHM for parameter change detection, the main one being the development of refined scales for structural condition assessment before any data from the changed state is available. Ultimately, the VoSHM is the benefit brought by adopting these refined scales in maintenance management.

On join-complete implication algebras

In this paper, first, we consider an algebra that has a binary operation and a join of arbitrary nonempty subset. A lattice implication algebra is a lattice with a binary operation, which has a join and a meet of finite nonempty subsets. In this work, the notion of join-complete implication algebras L is defined as a join-complete lattice with a binary operation, and some properties of this algebra L are searched. Moreover, we prove that the interval [a, 1] in L is a lattice implication algebra and show that L satisfies the completely distributive law when it has the smallest element 0. Finally, we state the concept of filter and multipliers of L and provide finite and infinite examples of them. In addition, we research some properties of these concepts in detail.

The Trusted Route to Environmental Responsibility

Filter Concept highlights how filtration technology is a crucial ally in the quest for sustainability

Optimal Node Routing Layouts in Mobile Adhoc Network

Mobile Adhoc Network (MANET) is a self-organizing network of various network devices responsible for communication. In MANET, new layouts are adopted for energy optimization, security implementation, traffic minimization and overhead reduction. MANET are aggressive in nature. This requires modification in network routing protocols for performance enhancement. This paper presents the detailed survey of different layouts involved in the implementation of network routing protocols in MANET. The survey is classified into four phases involved in MANET routing applications namely- routing protocols, neighborhood discovery, distributed or centralized hash tables, and bloom filter. Firstly, the classification of routing protocols based on various traffic models presents the MANET configuration. Secondly, a neighborhood discovery mechanism conveys the enhancement in the routing configurations. Thirdly, application of hash table operation (distributed/ centralized) to MANET to improve the matching efficiencies and computational speed. Finally, the application of bloom filter concept to improve service discovery rate and reduce the fake identities. Traditionally, the unpredictability occurs during the prediction of optimal node routing due to the dynamic nature of the MANET. Moreover, the presence of ejected malicious node in another cluster disgraced the link stability. This survey conveys the problems such as storage overhead, mobility nature, malicious nodes, and false positive rates in the traditional methods. The detailed survey leads to the stone of integration of Distributed Hash Table (DHT) with a bloom filter to reduce the problems in traditional research works. Index Terms – Performance Optimization, Bloom Filter, Centralized Hash Table (CHT), Distributed Hash Table (DHT), Energy Consumption, Mobile Ad- hoc Network (MANET), Quality of Service (QoS), Routing.

Ideals and Filters on Neutrosophic Topologies Generated by Neutrosophic Relations

Recently, Milles and Hammami presented and studied the concept of a neutrosophic topology generated by a neutrosophic relation. As a continuation in the same direction, this paper studies the concepts of neutrosophic ideals and neutrosophic filters on that topology. More precisely, we offer the lattice structure of neutrosophic open sets of a neutrosophic topology generated via a neutrosophic relation and examine its different characteristics. Furthermore, we enlarge to this lattice structure the notions of ideals (respectively, filters) and characterize them with regard to the lattice operations. We end this work by studying the prime neutrosophic ideal and prime neutrosophic filter as interesting types of neutrosophic ideals and neutrosophic filters.

Congruences and Filters of BH-Lattices

In this paper, we introduce the concept of filters in BH-lattices and furnish certain examples. We obtain certain basic properties of BH-lattices. Further, we characterize the filter generated by a given sub set of a BH-lattice. Also we prove that, the set of all filters with set inclusion forms a Heyting algebra. We obtain a one to one correspondence between the set of congruences and filter of BH-lattices.

Real-time application and modelling of the NOx-sorption reaction on a particulate calcium carbonate surface-flow filter exposed to combustion exhaust.

Of major interest, especially in city environments, and increasingly inside vehicles or industrial plants, is the drive to reduce human exposure to nitrogen oxides (NOx). This trend has drawn increasing attention to filtration, which has developed remarkably owing to the capabilities of recently developed mathematical models and novel filter concepts. This paper reports on the study of the kinetic modelling of adsorption of nitrogen dioxide (NO2), collected from the tailpipe of a diesel engine, reacting to calcium nitrate salt (Ca(NO3)2) on a surface flow filter consisting of a coating of fine ground limestone or marble (CaCO3) in combination with micro-nanofibrillated cellulose (MNFC) acting as binder and humectant applied onto a multiply recycled newsprint substrate. The coating and substrate are both porous, but on different pore size scales, with the coating having significantly lower permeability. To maximise gas-coating contact, therefore, the coating deposition is pixelated, achieved by pin coating. An axially dispersed gaseous plug flow model (dispersion model) was used to simulate the transport within the coating pore network structure, following earlier flow modelling studies, and a kinetic reaction model was used to examine NO2 to NO3- conversion in correlation with experimental results. Modelling results indicate a 60.38% conversion of exposed NO2 gas to Ca(NO3)2 under the specific conditions applied, with an absolute relative error between the predicted and experimentally estimated value being 0.81%. The model additionally enabled a prediction of effects of changing parameters over a limited perturbation range, thus assisting in predicting filter element consumption, with attention given to the active component CaCO3 surface as a function of particle size in relation to the gas contact exchange, promoting the reaction over time. It is intended that the Ca(NO3)2 formed from the reaction can go on to be used as a value-added fertiliser, thus contributing to circular economy.

Exploiting the entire near-infrared spectral range to improve the detection of methane plumes with high-resolution imaging spectrometers

Abstract. Remote sensing emerges as an important tool for the detection of methane plumes emitted by so-called point sources, which are common in the energy sector (e.g., oil and gas extraction and coal mining activities). In particular, satellite imaging spectroscopy missions covering the shortwave infrared part of the solar spectrum are very effective for this application. These instruments sample the methane absorption features at the spectral regions around 1700 and 2300 nm, which enables the retrieval of methane concentration enhancements per pixel. Data-driven retrieval methods, in particular those based on the matched filter concept, are widely used to produce maps of methane concentration enhancements from imaging spectroscopy data. Using these maps enables the detection of plumes and the subsequent identification of active sources. However, retrieval artifacts caused by particular surface components may sometimes appear as false plumes or disturbing elements in the methane maps, which complicates the identification of real plumes. In this work, we use a matched filter that exploits a wide spectral window (1000–2500 nm) instead of the usual 2100–2450 nm window with the aim of reducing the occurrence of retrieval artifacts and background noise. This enables a greater ability to discriminate between surface elements and methane. The improvement in plume detection is evaluated through an analysis derived from both simulated data and real data from areas including active point sources, such as the oil and gas (O&G) industry from San Joaquin Valley (US) and the coal mines from the Shanxi region (China). We use datasets from the Precursore IperSpettrale della Missione Applicativa (PRISMA) and the Environmental Mapping and Analysis Program (EnMAP) satellite imaging spectrometer missions and from the Airborne Visible/Infrared Imaging Spectrometer – Next Generation (AVIRIS-NG) instrument. We find that the interference with atmospheric carbon dioxide and water vapor is generally almost negligible, while co-emission or overlapping of these trace gases with methane plumes leads to a reduction in the retrieved concentration values. Attenuation will also occur in the case of methane emissions situated above surface structures that are associated with retrieval artifacts. The results show that the new approach is an optimal trade-off between the reduction in background noise and retrieval artifacts. This is illustrated by a comprehensive analysis in a PRISMA dataset with 15 identified plumes, where the output mask from an automatic detection algorithm shows an important reduction in the number of clusters not related to CH4 emissions.

Recognising interdisciplinary implications of the affective filter

Linguistic education, like practically any other form of education, is strongly determined by affect. Although the entire “story” is far more complex, we might summarise it by saying that if students and teachers find themselves in emotionally convenient circumstances, linguistic progress is easily noticeable, whereas in situations when either of them are experiencing negative feelings or emotions, linguistic efforts are likely to prove simply futile. As implied by the well-known concept of the affective filter, negative emotions – be it fear, anxiety, discomfort and such – act an invisible wall blocking cognition and disable linguistic education. Hence, the teachers’ and – predominantly – the students’ affect either aids or hinders education and it does so in a less or more concealed fashion. On the level of terminology, too, the presence and salience of affect is either explicit or implicit. The former is the case with the said notion of affective filter and others such as speech anxiety, emotional intelligence, willingness to communicate, everyday stressors, etc. The latter is even more extensive, although it tends to be overlooked or disregarded, which can be exemplified by such linguistic concepts as, for example, (a) fossilization, which is mostly defined in cognitive terms and relates to that part of language users’ competence which has become fixed and may fall subject to stagnation – but which results from our natural need of comfort and of social recognition; or even such a traditional term as (b) language performance, which is contrasted against language competence and also viewed through a predominantly cognitive prism – but which, too, is subject to our emotional stance and individual invariably-unstable and internally influential feelings.

A Fuzzy Semibipolar Soft Filter and its Association with Green's Relation $\mathcal{N}$

This paper introduces the concept of fuzzy semibipolar soft filters in ordered groupoids. It is defined in the form of fuzzy semibipolar soft sets over universal sets. Then, a corresponding example is proposed. A necessary and sufficient condition for fuzzy semibipolar soft filters is provided. Finally, Green's relation $\mathcal{N}$ on ordered groupoids is described in terms of fuzzy semibipolar soft filters.

SR-fuzzy filters in Sheffer stroke BL-algebras

The concepts of SR-fuzzy quasi-subalgebras and (ultra) SR-fuzzy filters over Sheffer stroke BL-algebras are introduced for the study of quasi-subalgebras and (ultra) filters using the SR-fuzzy set, and various properties are investigated accordingly. The relationship between SR-fuzzy quasi-subalgebras and SR-fuzzy filters is considered, and the characterizations of an (ultra) SR-fuzzy filter are discussed.

In-ADC, Rank-Order Filter for Digital Pixel Sensors

This paper presents a new implementation of the rank-order filter, which is established on a parallel-operated array of single-slope (SS) analog-to-digital converters (ADCs). The SS ADCs use an “on-the-ramp processing” technique, i.e., filtration is performed along with analog-to-digital conversion, so the final states of the converters represent a filtered image. A proof-of-concept 64 × 64 array of SS ADCs, integrated with MOS photogates, was fabricated using a standard 180 nm CMOS process. The measurement results demonstrate the full functionality of the novel filter concept, with image acquisition in both single-sampling and correlated-double-sampling (CDS) modes (CDS is digitally performed using ADCs). The experimental, massively parallel rank-order filter can process 650 frames per second with a power consumption of 4.81 mW.

Systematic use of nonlinear data filtering methods in forecasting tasks

The article describes an approach to the systematic use of nonlinear data filtering methods in tasks of intelligent data analysis and machine learning. The concepts of filtering and non-linear filtering are considered. The analysis of modern methods of optimal and probabilistic nonlinear filtering of statistical data and the peculiarities of their application in solving the problems of estimating the states of dynamic systems is carried out. The application of the Kalman filter and its variants for solving nonlinear filtering problems is analysed. The classification of nonlinear filtering methods is given. In the basis of the classification are digital, optimal and probabilistic filters. Non-recursive and recursive digital filters are studied. The formulation of the problem of optimal filtering based on the Kalman filter is considered. The filtering equation for a free dynamic system based on the state space model of a discrete system is given. The extended Kalman filter and its modifications are considered. The Bayesian method of estimating the state of a nonlinear stochastic system is presented. The problem of linear and nonlinear probabilistic filtering is considered. Three filters are considered as examples of probabilistic filters: an unscented Kalman filter, a point mass filter, and a granular filter. The granular filtering algorithm and its modifications are considered in detail. The architecture of the information-analytical system for solving forecasting problems has been developed. The system consists of the following main components: user interface, information storage subsystem, data analysis and pre-processing subsystem, modelling subsystem, forecast construction and evaluation subsystem, visualization subsystem. As an example of forecasting based on the systematic use of non-linear filtering methods, the task of forecasting the prices of Google shares is considered. A comparison of the quality assessment results of basic models and forecast values without filtering and with different options for applying filters was carried out. To improve the quality of forecasting based on prepared data and based on nonlinear filtering methods, a method based on combined forecasts was used to solve the forecasting problem. The results of forecasting using the combined model are presented

Open Hardware Implementation of Real-Time Phase and Amplitude Estimation for Neurophysiologic Signals.

Adaptive deep brain stimulation (aDBS) is a promising concept in the field of DBS that consists of delivering electrical stimulation in response to specific events. Dynamic adaptivity arises when stimulation targets dynamically changing states, which often calls for a reliable and fast causal estimation of the phase and amplitude of the signals. Here, we present an open-hardware implementation that exploits the concepts of resonators and Hilbert filters embedded in an open-hardware platform. To emulate real-world scenarios, we built a hardware setup that included a system to replay and process different types of physiological signals and test the accuracy of the instantaneous phase and amplitude estimates. The results show that the system can provide a precise and reliable estimation of the phase even in the challenging scenario of dealing with high-frequency oscillations (~250 Hz) in real-time. The framework might be adopted in neuromodulation studies to quickly test biomarkers in clinical and preclinical settings, supporting the advancement of aDBS.