Filtration Scheme Research Articles

Intelligent multimodal medical image fusion with deep guided filtering

Medical image fusion is a synthesis of visual information present in any number of medical imaging inputs into a single fused image without any distortion or loss of detail. It enhances image quality by retaining specific features to improve the clinical applicability of medical imaging for treatment and evaluation of medical conditions. A big challenge in the processing of medical images is to incorporate the pathological features of the complement into one image. The fused image presents various challenges, such as existence of fusion artifacts, hardness of the base, comparison of medical image input, and computational cost. The techniques of hybrid multimodal medical image fusion (HMMIF) have been designed for pathologic studies, such as neurocysticercosis, degenerative and neoplastic diseases. Two domain algorithms based on HMMIF techniques have been developed in this research for various medical image fusion applications for MRI-SPECT, MRI-PET, and MRI-CT. NSCT is initially used in the proposed method to decompose the input images which give components of low and high frequency. The average fusion rule applies to NSCT components with low frequency. The NSCT high frequency components are fused by the law of full fusion. NSCTs high frequency is handled with directed image filtration scheme. The fused picture is obtained by taking inverse transformations from all frequency bands with the coefficients obtained from them. The methods suggested are contrasted with traditional approaches in the state of the art. Experimentation proves that the methods suggested are superior in terms of both qualitative and quantitative assessment. The fused images using proposed algorithms provide information useful for visualizing and understanding the diseases to the best of both sources’ modality.

A complementary filter consisting of a GPS-receiver and an accelerometer

Complementary filters have become widely used to measure the angular position of moving objects in space due to their simplicity and high accuracy. If at first they were used mainly in navigation systems, now they are beginning to be widely used in navigation systems. In such complementary filters, the complementary filter most often includes a GPS receiver and an accelerometer. The problem of reducing the influence of high-frequency interference of the GPS receiver on the accuracy of the system is considered. Direct filtering of the output signal of the GPS receiver has a significant disadvantage, which is the delay of the filter of the measured signal. This is often the main obstacle of using filters. Complementary filters due to the combination of two meters make it possible to filter the signal without affecting the passage of the useful signal. This is the main advantage of complementary filters. It should also be noted that they are very simple to implement, which has led to the widespread use of complementary filters in systems for measuring the motion of objects. The paper proposes a second-order filter structure in which there is no integration of the accelerometer signal that significantly simplifies the implementation of the filter and eliminates the problem of the influence of the non-zero accelerometer signal. The presence of zero offset accelerometer and integration procedures is one of the main problems in solving navigation problems.
 In the absence of an integrator, the question arises of taking into account the initial value of the output signal of the GPS receiver. This issue in the work is solved by the circuit method. In complementary filters built on the compensation scheme, this problem is solved quite simply. The article considers a simpler complementary filter, built on the filtration scheme. An algorithm for taking into account the initial conditions is proposed for such a filter structure. The influence of the structure of the transfer functions of the filter on the efficiency of its use is analyzed. It is shown that the complementary filter can significantly reduce the influence of high-frequency noise of the GPS receiver. The block diagram of the filter in the Matlab-Simulink environment and the simulation results that show the effectiveness of the proposed complementary filter structure are presented.
 Such systems can be used in small moving objects like UAVs, in robotics, in the educational process.

Rolling element bearing fault identification using a novel three-step adaptive and automated filtration scheme based on Gini index

For early detection of rolling element bearings (REBs) faults in contaminated signals, kurtosis-derived indices are involved in the filtration process prior to demodulation. However, they were found either sensitive to impulsive outliers or requiring many input arguments. In this study, a novel three-step adaptive and automated filtration scheme using Gini index (GI) is proposed as an alternative to kurtosis-based techniques to enhance the weak fault features and eliminate noise and interferences from the raw vibration signal. The proposed approach was tested using experimental signals with different bearing faults. The filtered signals were greatly denoised and the fault impulses were successfully isolated, which indicates the effectiveness of the proposed approach and the superiority of GI over kurtosis-derived indices as a criterion for proper filter design for REBs fault detection.

Mathematical model filtering canonical parameters of satellite-repeater in orbital motion

For the effective solution of the problem estimation of canonical parameters the satellite-repeater at orbital motion the substantial statement within which the generalized scheme of model filtration of coordinates and a vector of speed movement the satellite-repeater is given is formulated. The system of restrictions and assumptions is introduced. When the state vector is represented by a continuous vector Markov process, the generalized equations of state and observations in kinematic variables are determined. Using the methods of numerical differentiation, schemes for solving ordinary differential equations, optimization, linearization of the original filtration problem in determining the rules for calculating the evolution and measurement matrices is performed. The efficiency of the generated algorithmic solutions is tested on specific examples.

Persistent homology of unweighted complex networks via discrete Morse theory

Topological data analysis can reveal higher-order structure beyond pairwise connections between vertices in complex networks. We present a new method based on discrete Morse theory to study topological properties of unweighted and undirected networks using persistent homology. Leveraging on the features of discrete Morse theory, our method not only captures the topology of the clique complex of such graphs via the concept of critical simplices, but also achieves close to the theoretical minimum number of critical simplices in several analyzed model and real networks. This leads to a reduced filtration scheme based on the subsequence of the corresponding critical weights, thereby leading to a significant increase in computational efficiency. We have employed our filtration scheme to explore the persistent homology of several model and real-world networks. In particular, we show that our method can detect differences in the higher-order structure of networks, and the corresponding persistence diagrams can be used to distinguish between different model networks. In summary, our method based on discrete Morse theory further increases the applicability of persistent homology to investigate the global topology of complex networks.

Volume-of-interest imaging with dynamic fluence modulation using multiple aperture devices.

Volume-of-interest (VOI) imaging is a strategy in computed tomography (CT) that restricts x-ray fluence to particular anatomical targets via dynamic beam modulation. This permits dose reduction while retaining image quality within the VOI. VOI-CT implementation has been challenged, in part, by a lack of hardware solutions for tailoring the incident fluence to the patient and anatomical site, as well as difficulties involving interior tomography reconstruction of truncated projection data. We propose a general VOI-CT imaging framework using multiple aperture devices (MADs), an emerging beam filtration scheme based on two binary x-ray filters. Location of the VOI is prescribed using two scout views at anterior-posterior (AP) and lateral perspectives. Based on a calibration of achievable fluence field patterns, MAD motion trajectories were designed using an optimization objective that seeks to maximize the relative fluence in the VOI subject to minimum fluence constraints. A modified penalized-likelihood method is developed for reconstruction of heavily truncated data using the full-field scout views to help solve the interior tomography problem. Physical experiments were conducted to show the feasibility of noncentered and elliptical VOI in two applications-spine and lung imaging. Improved dose utilization and retained image quality are validated with respect to standard full-field protocols. We observe that the contrast-to-noise ratio (CNR) is 40% higher compared with low-dose full-field scans at the same dose. The total dose reduction is 50% for equivalent image quality (CNR) within the VOI.

Volume-of-interest Imaging Using Multiple Aperture Devices.

Volume-of-interest (VOI) imaging is a promising strategy for dose reduction in computed tomography (CT) while retaining image quality. However, implementation of VOI-CT has been challenged by the lack of adequate hardware and the interior tomography reconstruction problem. Multiple aperture devices (MAD) are a novel filtration scheme that can achieve x-ray fluence field modulation in a compact design with small translations. In this work, we propose a general approach for VOI imaging using MADs. MAD trajectories are designed to dynamically tailor the fluence for prescribed VOI. A penalized-likelihood reconstruction algorithm is proposed for fully truncated projections extended with scout views. Physical experiments were conducted to verify the feasibility for non-centered elliptic VOIs. Image quality and dose were estimated and compared with standard fullfield protocols. The ability of MAD-based VOI imaging to retain high image quality while significantly decreasing the total dose is demonstrated, suggesting the potential for dose reduction in clinical CT applications.

Capillary Nanofiltration under Anoxic Conditions as Post-Treatment after Bank Filtration

Bank filtration schemes for the production of drinking water are increasingly affected by constituents such as sulphate and organic micropollutants (OMP) in the source water. Within the European project AquaNES, the combination of bank filtration followed by capillary nanofiltration (capNF) is being demonstrated as a potential solution for these challenges at pilot scale. As the bank filtration process reliably reduces total organic carbon and dissolved organic carbon (DOC), biopolymers, algae and particles, membrane fouling is reduced resulting in long term operational stability of capNF systems. Iron and manganese fouling could be reduced with the possibility of anoxic operation of capNF. With the newly developed membrane module HF-TNF a good retention of sulphate (67–71%), selected micropollutants (e.g., EDTA: 84–92%) and hardness (41–55%) was achieved together with further removal of DOC (82–87%). Fouling and scaling could be handled with a good cleaning concept with acid and caustic. With the combination of bank filtration and capNF a possibility for treatment of anoxic well water without further pre-treatment was demonstrated and retention of selected current water pollutants was shown.

Mathematical Modeling of Solutes Migration under the Conditions of Groundwater Filtration by the Model with the k-Caputo Fractional Derivative

Within the framework of a new mathematical model of convective diffusion with the k-Caputo derivative, we simulate the dynamics of anomalous soluble substances migration under the conditions of two-dimensional steady-state plane-vertical filtration with a free surface. As a corresponding filtration scheme, we consider the scheme for the spread of pollution from rivers, canals, or storages of industrial wastes. On the base of a locally one-dimensional finite-difference scheme, we develop a numerical method for obtaining solutions of boundary value problem for fractional differential equation with k-Caputo derivative with respect to the time variable that describes the convective diffusion of salt solution. The results of numerical experiments on modeling the dynamics of the considered process are presented. The results that show an existence of a time lag in the process of diffusion field formation are presented.

Improvements to the Rice Genome Annotation Through Large-Scale Analysis of RNA-Seq and Proteomics Data Sets.

Rice (Oryza sativa) is one of the most important worldwide crops. The genome has been available for over 10 years and has undergone several rounds of annotation. We created a comprehensive database of transcripts from 29 public RNA sequencing data sets, officially predicted genes from Ensembl plants, and common contaminants in which to search for protein-level evidence. We re-analyzed nine publicly accessible rice proteomics data sets. In total, we identified 420K peptide spectrum matches from 47K peptides and 8,187 protein groups. 4168 peptides were initially classed as putative novel peptides (not matching official genes). Following a strict filtration scheme to rule out other possible explanations, we discovered 1,584 high confidence novel peptides. The novel peptides were clustered into 692 genomic loci where our results suggest annotation improvements. 80% of the novel peptides had an ortholog match in the curated protein sequence set from at least one other plant species. For the peptides clustering in intergenic regions (and thus potentially new genes), 101 loci were identified, for which 43 had a high-confidence hit for a protein domain. Our results can be displayed as tracks on the Ensembl genome or other browsers supporting Track Hubs, to support re-annotation of the rice genome.

Persistent homology for object segmentation in multidimensional grayscale images

In this paper, we develop a methodology originating from algebraic topology, and we demonstrate its capability of performing multidimensional object segmentation without the need of prior parameters. Persistent homology is a method used in algebraic topology to study qualitative features of data that persist across varying scales. The construction of a topological complex on the image is followed by a filtration scheme that consists of composing a nested sequence of cell complexes on which the persistent homology is computed. The most persistent homology classes are extracted by identifying 1D and 2D chains with large lifespans, which allows salient objects in 2D and 3D images to be segmented and detected. A comparison between this method and other segmentation techniques on a synthetic image shows the advantages of the proposed method. The strength of this technique is reflected in its insensitivity to continuous deformations and perturbations of the input function and in its independence of prior parameters. The results obtained on real and biomedical 2D and 3D images also demonstrate the potential of this method.

Riverbank filtration: a case study of four sites in the hilly regions of Uttarakhand, India

Riverbank filtration (RBF) schemes based on the filtration of the river water through adjacent aquifers have been successfully implemented in the plains globally. In the mountainous regions, alluvial aquifers are generally narrow and restricted to the riverbanks. The present study assesses the possibility and potential of RBF in the lower Himalayan region for drinking water supply. Production wells (18–30 m deep) were commissioned on the banks of the rivers (1) Alaknanda in Srinagar (546 m a.m.s.l.) and Kaleshwar (Karnaprayag; 778 m a.m.s.l.); (2) East Nayar in Satpuli (576 m a.m.s.l.) and (3) Mandakini in Agastyamuni (783 m a.m.s.l.) in Uttarakhand, India. Waters from the rivers, production wells, and hand pumps were analyzed for major ions, coliforms and stable isotopes (δ18O and δ2H). The wells delivered coliform- and turbidity-free water even during monsoon. The proportion of the bank filtrate was site specific and also varied from monsoon to non-monsoon periods. The Satpuli scheme draws almost completely bank filtrate round the year. The other three schemes substantially draw groundwater and its proportion increases in monsoon. In Srinagar, the well water was chemically similar to the ground water but isotopically similar to the river water. The region also has a complex hydrology with paths that deliver river water containing coliforms and even suspended silt up to ~ 0.5 km inland. A severe flooding event during the study period affected the RBF sites in Srinagar and Kaleshwar, thereby indicating the need to make RBF wells flood proof. In general, the study shows RBF to be an effective and sustainable option to supply drinking water in a few regions of lower Himalayas.

Virus reduction through microfiltration membranes modified with a cationic polymer for drinking water applications

Virus penetration is a significant problem in water treatment membrane filtration. To effectively remove waterborne viruses nano-filtration, reverse osmosis or ultrafiltration must be used, all of which are high energy filtration schemes. Novel approaches and technologies for the production of virus-free drinking water are therefore warranted. In this study, we modified model surfaces and commercial polyether sulfone, (PES) microfiltration (MF) membranes to achieve a substantial virus reduction under gravity based filtration membranes. The successful modification using the cationic polymer polyethyleneimine (PEI) was confirmed by Fourier transform infrared spectroscopy (FTIR) and zeta potential measurements. MS2 bacteriophages, a surrogate for human pathogenic waterborne viruses like norovirus were used to challenge the modified surfaces. The membrane modification resulted in ∼22% loss of the membrane permeability while an increase of ≥3 log10-units (≥99.9%) in MS2 reduction was observed. These reductions were comparable to the reduction of PEI-coated model surfaces tested for contact reduction. This simple modification of a commercially available MF membrane led to substantial viral reductions with a significant flux of 5000 L/m2 in approximately 2.5 h. This work therefore, highlights the potential modified MF membranes for gravity-based filtrations to produce safe drinking water. Further studies should be done to show similarly enhanced reductions of human pathogenic viruses.

Assessment of single‐instrument techniques for removing wave bias from Reynolds stress estimates

AbstractA new single‐instrument method for removing wave bias from Reynolds stress estimates is proposed. Assuming that the wave motions and the pressure signal are spatially coherent, the method uses a linear filtration scheme to estimate the wave velocity at the instrument based on the pressure signal, and then the estimated velocity is subtracted from the measured velocity to arrive at a wave‐free estimate of the Reynolds stress. The advantage of the proposed single‐instrument technique is that it limits the financial and logistical issues associated with deploying a second instrument. The proposed method is compared to two frequency‐domain‐based single‐instrument techniques and to a two‐instrument method that uses the velocity signal at an adjacent instrument in a linear filtration scheme to estimate and remove the wave velocity. The methods are tested and compared using synthetic time series and field data collected in tidally driven shallow water flow in Wassaw Sound, Georgia and in deeper water currents in Monterey Bay, California. The method proposed in this study offers superior performance over the other single‐instrument techniques in shallow water, comparing favorably with the two‐instrument method. In deeper water, no single‐instrument technique offers clearly superior performance.

Validating and implementing modified Filinov phase filtration in semiclassical dynamics.

The Mixed Quantum-Classical Initial Value Representation (MQC-IVR) is a recently introduced approximate semiclassical (SC) method for the calculation of real-time quantum correlation functions. MQC-IVR employs a modified Filinov filtration (MFF) scheme to control the overall phase of the SC integrand, extending the applicability of SC methods to complex systems while retaining their ability to accurately describe quantum coherence effects. Here, we address questions regarding the effectiveness of the MFF scheme in combination with SC dynamics. Previous work showed that this filtering scheme is of limited utility in the context of semiclassical wavepacket propagation, but we find that the MFF is extraordinarily powerful in the context of correlation functions. By examining trajectory phase and amplitude contributions to the real-time SC correlation function in a model system, we clearly demonstrate that the MFF serves to reduce noise by damping amplitude only in regions of highly oscillatory phase leading to a reduction in computational effort while retaining accuracy. Further, we introduce a novel and efficient MQC-IVR formulation that allows for linear scaling in computational cost with the total simulation length, a significant improvement over the more-than quadratic scaling exhibited by the original method.

Produced water re-injection in a non-fresh water aquifer with geochemical reaction, hydrodynamic molecular dispersion and adsorption kinetics controlling: model development and numerical simulation

An improved produced water reinjection (PWRI) model that incorporates filtration, geochemical reaction, molecular transport, and mass adsorption kinetics was developed to predict cake deposition and injectivity performance in hydrocarbon aquifers in Nigeria oil fields. Thus, the improved PWRI model considered contributions of geochemical reaction, adsorption kinetics, and hydrodynamic molecular dispersion mechanism to alter the injectivity and deposition of suspended solids on aquifer wall resulting in cake formation in pores during PWRI and transport of active constituents in hydrocarbon reservoirs. The injectivity decline and cake deposition for specific case studies of hydrocarbon aquifers in Nigeria oil fields were characterized with respect to its well geometry, lithology, and calibrations data and simulated in COMSOL multiphysics software environment. The PWRI model was validated by comparisons to assessments of previous field studies based on data and results supplied by operator and regulator. The results of simulation showed that PWRI performance was altered because of temporal variations and declinations of permeability, injectivity, and cake precipitation, which were observed to be dependent on active adsorption and geochemical reaction kinetics coupled with filtration scheme and molecular dispersion. From the observed results and findings, transition time tr to cake nucleation and growth were dependent on aquifer constituents, well capacity, filtration coefficients, particle-to-grain size ratio, water quality, and more importantly, particle-to-grain adsorption kinetics. Thus, the results showed that injectivity decline and permeability damage were direct contributions of geochemical reaction, hydrodynamic molecular diffusion, and adsorption kinetics to the internal filtration mechanism, which are largely dependent on the initial conditions of concentration of active constituents of produced water and aquifer capacity.

Cost-Efficient Remote Backup Services for Enterprise Clouds

In order to efficiently achieve fault tolerance in cloud computing, large-scale data centers generally leverage remote backups to improve system reliability. Due to long-distance and expensive network transmission, the backups incur heavy communication overheads and potential errors. To address this important problem, we propose an efficient remote communication service, called Neptune. Neptune efficiently transmits massive data between long-distance data centers via a cost-effective filtration scheme. The filtration in Neptune is interpreted as eliminating redundancy and compressing similarity of files, which are generally studied independently in the existing work. In order to bridge their gap, Neptune leverages chunk-level deduplication to eliminate duplicate files and uses approximate delta compression to compress similar files. Moreover, in order to reduce the complexity and overheads, Neptune uses a locality-aware hashing to group similar files and proposes shortcut delta chains for fast remote recovery. We have implemented Neptune between two data centers and their distance is more than 1200 km via a 2 Mb/s network link. We examine the Neptune performance using real-world traces of Los Alamos National Laboratory (LANL), EMC, and Campus collection. Compared with state-of-the-art work, experimental results demonstrate the efficiency and efficacy of Neptune.

Impacts of extreme flooding on riverbank filtration water quality

Riverbank filtration schemes form a significant component of public water treatment processes on a global level. Understanding the resilience and water quality recovery of these systems following severe flooding is critical for effective water resources management under potential future climate change. This paper assesses the impact of floodplain inundation on the water quality of a shallow aquifer riverbank filtration system and how water quality recovers following an extreme (1 in 17year, duration >70days, 7day inundation) flood event. During the inundation event, riverbank filtrate water quality is dominated by rapid direct recharge and floodwater infiltration (high fraction of surface water, dissolved organic carbon (DOC) >140% baseline values, >1 log increase in micro-organic contaminants, microbial detects and turbidity, low specific electrical conductivity (SEC) <90% baseline, high dissolved oxygen (DO) >400% baseline). A rapid recovery is observed in water quality with most floodwater impacts only observed for 2–3weeks after the flooding event and a return to normal groundwater conditions within 6weeks (lower fraction of surface water, higher SEC, lower DOC, organic and microbial detects, DO). Recovery rates are constrained by the hydrogeological site setting, the abstraction regime and the water quality trends at site boundary conditions. In this case, increased abstraction rates and a high transmissivity aquifer facilitate rapid water quality recoveries, with longer term trends controlled by background river and groundwater qualities. Temporary reductions in abstraction rates appear to slow water quality recoveries. Flexible operating regimes such as the one implemented at this study site are likely to be required if shallow aquifer riverbank filtration systems are to be resilient to future inundation events. Development of a conceptual understanding of hydrochemical boundaries and site hydrogeology through monitoring is required to assess the suitability of a prospective riverbank filtration site.

Breaking Down Chemical Weapons by Metal–Organic Frameworks

Seek and destroy: Filtration schemes and self-detoxifying protective fabrics based on the Zr(IV)-containing metal-organic frameworks (MOFs) MOF-808 and UiO-66 doped with LiOtBu have been developed that capture and hydrolytically detoxify simulants of nerve agents and mustard gas. Both MOFs function as highly catalytic elements in these applications.

Параметризація схем обробки УЗД сонних артерій за допомогою еволюційних алгоритмів.

Nowadays, a lot of methods or sequences of image processing algorithms or, in other words, image processing schemes have been designed. Automatic selection of an image segmentation method (scheme) presupposes the existence of some rule which establishes a correspondence between a scheme (processing algorithms sequence) and the values of current image parameters. These rules allow parameterizing methods (schemes). So, there is a problem of determination of such rules. The solution of this problem is formalized and presented in the given paper. The parameterization of segmentation methods has been performed on the basis of an evolutionary algorithm. The algorithm searches for some set of texture parameters and their ranges. It allows us to assign some subspace in the whole space of all the texture parameters to each filtration scheme. Textural parameters are calculated on the basis of gray-level co-occurrence matrices. The proposed algorithm has been implemented and tested. 325 different image processing schemes have been used to test the algorithm. The comparison of different versions of the proposed algorithm has been conducted. The optimal parameters of evolutionary algorithms have been chosen: mutation probability, crossover probability, population size, number of generations, number of simultaneously developing populations, as well as the percentage of genes which are being activated on the initial step of population generation. Testing has been conducted on the basis of texture parameter values of ultrasound images of human carotid arteries.