Filter Window Research Articles

Clinical Application of DynaCT in the Study of Vascular Neointimal Hyperplasia Characteristics after Option Filter Placement.

The objective of this study was to analyze neointimal hyperplasia of the inferior vena cava (IVC) after Option filter implantation by DynaCT and to provide a reference for the safety of effective neointimal hyperplasia cutting after long retrieval window filter implantation in vivo. Clinical data on 22 patients with Option filters were retrospectively analyzed. DynaCT was used to analyze the characteristics of neointimal hyperplasia after filter implantation, including the distribution of neointimal hyperplasia and the maximum thickness of the neointimal hyperplasia. Correlation analysis was performed between the measurement results and the number of times the inner membrane of the filter was cut during filter retrieval, and correlation analysis also was performed between the measurement results and the time of filter placement. As measured by DynaCT, the neointimal hyperplasia after filter placement was located around the barbs of the filter plug, and the maximum neointimal hyperplasia thickness was located in the 1 to 5 points of the IVC. There was a linear trend between neointimal hyperplasia thickness of the IVC and filter neointimal cutting times by the retrieval catheter after filter placement. Correlation analysis showed a correlation coefficient of r = 0.609 (P = 0.003), indicating a significant correlation between the two. There also was a linear trend between neointimal hyperplasia thickness and implantation time. Correlation analysis showed that the correlation coefficient was r = 0.36 (P = 0.102), and the correlation between the two was not significant. Based on DynaCT, the characteristics of IVC neointimal hyperplasia after Option filter implantation were analyzed, and the cutting force and direction of neointimal hyperplasia could be controlled effectively and safely by changing the filter retrieval catheter. we can effectively and safely cut the hyperplastic intima by modifying the filter retrieval catheter to control the cutting force and direction and provide a reference for the safe and effective retrieval of the long-retrieval-time window filter after implantation in the body.

Total Magnetic Field Perturbations at Martian Low Altitudes (≤500 km): MAVEN Observations in 2014–2023

AbstractMagnetic perturbations in the Martian ionosphere are often considered as representing plasma irregularities, but thorough statistical comparisons between the two independent phenomena have been rarely conducted. In this study, we investigate the statistical relationship between total magnetic field perturbations and those of O2+ density as observed by the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft at altitudes below 500 km in 2014–2023. From the 1 Hz time series of magnetic field strength, perturbation intensity is estimated by subtracting a signal smoothed with a Savitzky‐Golay filter (window size ∼36 km). Statistically, the magnetic perturbations are stronger on the dayside than at night, in the local summer hemisphere than in winter, and away from crustal magnetic anomalies than nearby. Also, day‐to‐day variability of the magnetic perturbations exhibits a weak but significant correlation with that of solar wind electron density. The statistical behavior of total magnetic field perturbations is not the same as that of O2+ density perturbations: that is, the former is not a perfect proxy for the latter. The seemingly counter‐intuitive discrepancy can be explained by effects of inhomogeneous background magnetic field strength (participating in total pressure balance across plasma perturbations) and localized ionospheric currents at altitudes unreachable by MAVEN.

Adaptive median filter salt and pepper noise suppression approach for common path coherent dispersion spectrometer

The Common-path Coherent-dispersion Spectrometer (CODES), an exoplanet detection instrument, executes high-precision Radial Velocity (RV) inversions by recording the phase shifts of interference fringes. Salt-and-pepper noise caused by factors such as improper operation of the CCD probe/analog-to-digital converter and strong dark currents may interfere with the phase information of the fringe. This lowers the quality of the interfering fringe image and significantly interferes with the RV’s inversion. In this study, an adaptive median filtering algorithm (CODESmF) based on submaximum and subminimum values is designed to eliminate the interference fringe image's salt-and-pepper noise as well as to reduce RV error. This allows the interference fringe image's phase information to be retained more completely. The algorithm consists of two major modules. Pixel Sub-extreme-based Filtered Noise Monitoring Module: discriminates signal pixels and noise pixels based on the submaximum and subminimum values of the pixels in the filtering window. Adaptive Median Filter Noise Suppression Module: the signal pixel is kept at the original value output, the noise pixel serves as the filtering window's center pixel, and the adaptive median filtering procedure is repeated numerous times with various filtering window sizes. According to the experimental findings, the CODESmF outperforms comparable algorithms and works better at recovering interference fringes. More than 90% of the phase/RV error caused by salt-and-pepper noise is typically eliminated by the CODESmF algorithm, and in certain circumstances, it can even remove roughly 98% of the phase error.

Analysis of the ion collection model in the ExB probe

An ExB probe is a pass-band velocity filter for an ion beam. The ExB probe measurement is related to the ion velocity distribution function (IVDF); however, the finite pass-band filter window size leads to differences in the true IVDF and measured ExB probe spectrum. We derive for the first time an analytical ExB probe transmittancy matrix and use it to examine differences in the IVDF and the probe spectrum. The probe spectra are compared to a synthetically defined test IVDF to study how probe geometry and ion species affect the differences. It is found that the difference in the probe spectrum and the true IVDF is dependent on the ion species, and the deviation is larger for heavier ions. The peak velocity of the spectrum was shifted by up to 13%, and the velocity spread was broadened by up to 276%. The relative ion species fraction is calculated from the probe spectra by two different methods and compared to the true fraction. Using the approach of this work, direct integration of the spectrum resulted in a 2% difference, while a more common approach from literature overestimated one ion species by 184%.

Coral Shoals Detection from Optical Satellite Imagery Using Deep Belief Network Algorithm: A Case Study for the Xisha Islands, South China Sea

Coral islands and reefs are formed by the cementation of the remains of shallow water reef-building coral polyps and other reef dwelling organisms in tropical oceans. They can be divided into coral islands, coral sandbanks, coral reefs, and coral shoals, of which, Coral shoals are located below the depth datum and are not exposed even at low tide, and sometimes are distributed at water depths exceeding 30 m. Satellite images with wide spatial–temporal coverage have played a crucial role in coral island and reef monitoring, and remote sensing data with multiple platforms, sensors, and spatial and spectral resolutions are employed. However, the accurate detection of coral shoals remains challenging mainly due to the depth effect, that is, coral shoals, especially deeper ones, have very similar spectral characteristics to the sea in optical images. Here, an optical remote sensing detection method is proposed to rapidly and accurately detect the coral shoals using a deep belief network (DBN) from optical satellite imagery. The median filter is used to filter the DBN classification results, and the appropriate filtering window is selected according to the spatial resolution of the optical images. The proposed method demonstrated outstanding performance by validating and comparing the detection results of the Yinli Shoal. Moreover, the expected results are obtained by applying this method to other coral shoals in the Xisha Islands, including the Binmei Shoal, Beibianlang, Zhanhan Shoal, Shanhudong Shoal, and Yongnan Shoal. This detection method is expected to provide the coral shoals’ information rapidly once optical satellite images are available and cloud cover and tropical cyclones are satisfactory. The further integration of the detection results of coral shoals with water depth and other information can effectively ensure the safe navigation of ships.

Label-free detection and profiling of individual solution-phase molecules.

Most chemistry and biology occurs in solution, in which conformational dynamics and complexation underlie behaviour and function. Single-molecule techniques1 are uniquely suited to resolving molecular diversity and new label-free approaches are reshaping the power of single-molecule measurements. A label-free single-molecule method2-16 capable of revealing details of molecular conformation in solution17,18 would allow a new microscopic perspective of unprecedented detail. Here we use the enhanced light-molecule interactions in high-finesse fibre-based Fabry-Pérot microcavities19-21 to detect individual biomolecules as small as 1.2 kDa, a ten-amino-acid peptide, with signal-to-noise ratios (SNRs) >100, even as the molecules are unlabelled and freely diffusing in solution. Our method delivers 2D intensity and temporal profiles, enabling the distinction of subpopulations in mixed samples. Notably, we observe a linear relationship between passage time and molecular radius, unlocking the potential to gather crucial information about diffusion and solution-phase conformation. Furthermore, mixtures of biomolecule isomers of the same molecular weight and composition but different conformation can also be resolved. Detection is based on the creation of a new molecular velocity filter window and a dynamic thermal priming mechanism that make use of the interplay between optical and thermal dynamics22,23 and Pound-Drever-Hall (PDH) cavity locking24 to reveal molecular motion even while suppressing environmental noise. New in vitro ways of revealing molecular conformation, diversity and dynamics can find broad potential for applications in the life and chemical sciences.

Optimizing Windowed Filters for Enhanced OFDM Performance in 5G Networks: A Comprehensive Analysis of PAPR, BER, and PSD

Optimizing Windowed Filters for Enhanced OFDM Performance in 5G Networks: A Comprehensive Analysis of PAPR, BER, and PSD

Low PAPR Filtered OFDM using Modified Selective Mapping

Wireless Communication has been witnessing generational change in the span of eight to ten years since it came in existence. From generation 1G to 3G and from 4G to 5G the telecommunication world has seen significant improvements along with enhanced performance with every passing year. The objective of research is to comprehensive study of Filtered Orthogonal Frequency Division Multiplexing (F-OFDM) as a promising waveform option for fifth-generation (5G) communications, distinguished by its capacity to suppress out-of-band emission (OOBE) and accommodate asynchronous transmission. Though there are many advantages but the challenge of a high peak-to-average power ratio (PAPR) among new waveform candidates can’t be ignored. To address this problem, the selective mapping technique is used as a key method to alleviate the elevated PAPR trend within multicarrier systems. This research put emphasis on applying selective mapping technique to overcome the high PAPR values in an F-OFDM system with different windowed filters such as kaiser, Nuttles blackman harris and Root raised cousine followed by a proposed Modified Selective mapping technique for further improved performance in terms of PAPR for the Filtered OFDM for different window functions in comparison with the conventional OFDM system, SLM F-OFDM system. Furthermore, PAPR performance is evaluated for all the three-system using the different window techniques analyzed for both systems, both with and without the SLM technique and Modified SLM technique to mitigate the PAPR disadvantage of the Filtered OFDM system. Simulation results underscore that F-OFDM enhanced by SLM and MSLM outperforms OFDM across PAPR.

An Underwater Localization Method Based on Visual SLAM for the Near-Bottom Environment

The feature matching of the near-bottom visual SLAM is influenced by underwater raised sediments, resulting in tracking loss. In this paper, the novel visual SLAM system is proposed in the underwater raised sediments environment. The underwater images are firstly classified based on the color recognition method by adding the weights of pixel location to reduce the interference of similar colors on the seabed. The improved adaptive median filter method is proposed to filter the classified images by using the mean value of the filter window border as the discriminant condition to retain the original features of the image. The filtered images are finally processed by the tracking module to obtain the trajectory of underwater vehicles and the seafloor maps. The datasets of seamount areas captured in the western Pacific Ocean are processed by the improved visual SLAM system. The keyframes, mapping points, and feature point matching pairs extracted from the improved visual SLAM system are improved by 5.2%, 11.2%, and 4.5% compared with that of the ORB-SLAM3 system, respectively. The improved visual SLAM system has the advantage of robustness to dynamic disturbances, which is of practical application in underwater vehicles operated in near-bottom areas such as seamounts and nodules.

A Fuzzy-PI Clock Servo with Window Filter for Compensating Queue-Induced Delay Asymmetry in IEEE 1588 Networks.

Clock synchronization is one of the popular research topics in Distributed Measurement and Control Systems (DMCSs). In most industrial fields, such as Smart Grid and Flight Test, the highest requirement for synchronization accuracy is 1 μs. IEEE 1588 Precision Time Protocol-2008 (PTPv2) can theoretically achieve sub-microsecond accuracy, but it relies on the assumption that the forward and backward delays of PTP packets are symmetrical. In practice, PTP packets will experience random queue delays in switches, making the above assumption challenging to satisfy and causing poor synchronization accuracy. Although using switches supporting the Transparent Clock (TC) can improve synchronization accuracy, these dedicated switches are generally expensive. This paper designs a PTP clock servo for compensating Queue-Induced Delay Asymmetry (QIDA), which can be implemented based on ordinary switches. Its main algorithm comprises a minimum window filter with drift compensation and a fuzzy proportional-integral (PI) controller. We construct a low-cost hardware platform (the cost of each node is within USD 10) to test the performance of the clock servo. In a 100 Mbps network with background (BG) traffic of less than 70 Mbps, the maximum absolute time error (max |TE|) does not exceed 0.35 μs, and the convergence time is about half a minute. The accuracy is improved hundreds of times compared with other existing clock servos.

An Empirical Evaluation of Adapting Hybrid Parameters for CNN-based Sentiment Analysis

Sentiment analysis aims to understand human emotions and perceptions through various machine-learning pipelines. However, feature engineering and inherent semantic gap constraints often hinder conventional machine learning techniques and limit their accuracy. Newer neural network models have been proposed to automate the feature learning process and enrich learned features with word contextual embeddings to identify their semantic orientations to address these challenges. This article aims to analyze the influence of different factors on the accuracy of sentiment classification predictions by employing Feedforward and Convolutional Neural Networks. To assess the performance of these neural network models, we utilize four diverse real-world datasets, namely 50,000 movie reviews from IMDB, 10,662 sentences from LightSide Movie_Reviews, 300 public movie reviews, and 1,600,000 tweets extracted from Sentiment140. We experimentally investigate the impact of exploiting GloVe word embeddings on enriching feature vectors extracted from sentiment sentences. Findings indicate that using larger dimensions of GloVe word embeddings increases the sentiment classification accuracy. In particular, results demonstrate that the accuracy of the CNN with a larger feature map, a smaller filter window, and the ReLU activation function in the convolutional layer was 90.56% using the IMDB dataset. In comparison, it was 80.73% and 77.64% using the sentiment140 and the 300 sentiment sentences dataset, respectively. However, it is worth mentioning that, with large-size sentiment sentences (LightSide’s Movie Reviews) and using the same parameters, only a 64.44% level of accuracy was achieved.

Heterogeneous features and deep learning networks fusion-based pest detection, prevention and controlling system using IoT and pest sound analytics in a vast agriculture system

Every country's foundation is its agricultural industry, which drives about half of global economic growth. Accurate farming is crucial for crop evaluation and pest control. Old-fashioned pest detection is unstable and gives inaccurate forecasts. These surveillance tactics are intrusive, expensive, and vulnerable to assumptions. Pest sounds can be caught with minimum effort by utilizing IoT networks. Deep learning algorithms, species distribution range assessments, and nature monitoring can automatically identify and categorize pest sounds. The IoT-driven computerized components in this research's unique pest identification system used machine learning on insect sound recordings. The Butterworth filter, Blackman and Flattop window, Ultraspherical Filter, Rife-Vincent Window, Cosine-Tapered Window, FFT, DFT, STFT, PNCC, RASTA-PLPCC, LSFCC, sound detectors, and PID sensors were employed. The intended study used the HFDLNet for training, testing, and validation, examining 7,200 pest sounds from 72 species to determine their unique characteristics and statistical attributes. The proposed model has 99.87 % accuracy, 99.96 % sensitivity, 99.88 % specificity, 99.96 % recall, 99.93 % F1 score, and 99.98 % precision. This study outperforms Inception-ResNet-v2, FRCNN ResNet-50, Fatser-PestNet, MD-YOLO, YOLOv5m, MAM-IncNet, and Xception. The suggested solution uses IoT networks and pest sound analysis to establish a pest preventive and management strategy and a solar-powered generator to power IoT devices across vast agricultural fields.

Adjacent object distorts the organ-of-interest in filtered back-projection tomographic image reconstruction: 'ramp filter' or 'reconstruction' artifact revisited.

To simulate the artifact caused by an adjacent object on organ-of-interest during filtered back-projection (FBP) tomographic reconstruction (the so-called "ramp filter" artifact) and to demonstrate the extent to which an organ-of-interest is influenced by such adjacent hot spot or attenuating object. Two simulations are conducted with two simplified phantoms: "hot spot" and "cardiac." First one is used to visualize effect of hot spot on its periphery. Second one is used to evaluate effect of nearby object (liver) on left ventricle (LV) as organ-of-interest. To generate sinograms, forward projection process is done with and without modeling radiation attenuation. FBP using windowed ramp filter is done. All slices are analyzed by plotting intensity profiles. In tomographic slices, there is a hypo-intense halo around presumed edge of object when compared to background intensity, more noticeable in phantoms with less blurring. Even with ramp filter applied, no halo is visible in FBP without attenuation for cardiac phantom. In contrast, in slices with considering attenuation, zones with different levels of count suppression on both sides of object are visualized instead. The most prominent one is between liver and LV in simulation with higher-attenuating object and higher activity. A single hot spot with sufficient amount of blurring does not distort its surroundings. Hot spots and attenuating objects near organ-of-interest, however, distort myocardial perfusion imaging. Artifactual defects are thus only created when attenuation is modeled during FBP, producing zones of count suppression between organ-of-interest and nearby object or hot spot.

Research laser scanning damage detection method in f-k domain for laminate composite material

The use of composite plate structures has become increasingly prevalent in industries such as civil engineering, aerospace, high-speed rail, automotive, and wind power. However, the propagation of ultrasonic Lamb waves in these structures is subject to multi-modal and frequency dispersion effects, which, coupled with the complicated anisotropic propagation mechanism of composite materials, makes it challenging to extract damage scatter signals without a health signal as a reference. In this study, we apply the frequency-wavenumber ( f- k) domain filter wavefront modal method to carbon fiber reinforced polymer (CFRP) materials and use a three-dimensional (3D) window function to achieve different modalities and their corresponding damage reflection signals in the absence of a reference dispersion curve. Single modal damage imaging is achieved using a common source method (CSM) by laser vibration scanning experiment. To effectively extract single modalities in laminate material damage detection, a 3D filter window function was constructed. Considering the skew angle correction, it can effectively remove the direct wave signal, so as to realize the imaging of the damage.

Delay-Tracking Loop for Frequency Estimation of Grid-Interfaced Inverter Under Distorted Conditions

Fast and accurate frequency estimation is difficult for grid-interfaced inverter under distorted grid conditions with off-nominal frequency. A popular solution considers the multiple second-order generalized integrator-based frequency-locked loop yet can hardly achieve a fast dynamic response under significant phase jump and voltage sag. Another solution uses an adaptive sliding window filter with an additional frequency estimator. However, it is challenging to handle numerical instability due to the adjusting marginally-stable resonator and the accumulation error. This letter proposes a delay-tracking loop to overcome these problems. This loop allows the delay length to track the frequency with an inherent harmonics rejection at off-nominal frequency. At the same time, the fast response speed is maintained, and the marginally stable resonator is avoided. Comparative experimental results validate the above claims.

Realizing multi-function absorptions through arbitrary octagonal meta-atoms.

Metasurface absorbers (MA) typically exhibit a single type of absorption function due to their regular structures. In this study, we propose an irregular MA structure with octagonal meta-atoms. The presence of eight vertices in each meta-atom allows for tunable coordinates and offers a multitude of degrees of freedom in terms of geometry. As a result, the proposed MA exhibits diverse functionalities, including perfect absorption, multi-peaks absorption, and high absorption with a filtering window. To predict the geometric parameters of the MA structure based on a given target absorption spectrum, as well as the inverse design of the structure using the absorption spectrum as input, we employ a deep neural network combined with the particle swarm optimization algorithm. Remarkably, the mean-square error for spectrum prediction and inverse design of the MA structure is found to be as low as 0.0008 and 0.0031, respectively. This study opens up new possibilities for designing irregular electromagnetic structures and holds great potential for applications in multifunctional metasurfaces and metamaterials.

Frequency properties of channeled spectropolarimetry: an information theory perspective.

Channeled spectropolarimetry (CSP) has emerged as a notable technique due to its unique capacity to instantaneously measure either the polarization state of light or the Mueller matrix of a sample over a broad spectral range. Leveraging the quasi-linear relation between phase retardances of thick birefringent retarders and wavenumber, the target signal undergoes wavelength encoding. For the first time, we present a theoretical framework for the general CSP from a perspective of information theory. This framework comprehensively addresses the frequency properties of CSP, encompassing signal bandwidth, modulation frequency, sampling relationships, and filter window width during the demodulation process. Drawing from the frequency properties of CSP, we establish a theoretical foundation that informs the design of versatile CSPs and evaluates their measurement capabilities. Simulations for both Stokes CSP and Mueller CSP validate the efficacy of the proposed approach.

Microcanonical windows on quantum operators

We discuss the construction of a microcanonical projection WOW of a quantum operator O induced by an energy window filter W, its spectrum, and the retrieval of canonical many-time correlations from it.

Climatology of Martian Ionospheric Disturbances Deduced From MAVEN Data in 2014–2023

AbstractWe investigate the climatology of Martian ionospheric disturbances using Mars Atmosphere and Volatile Evolution missioN (MAVEN) data in 2014–2023. The disturbance strength is estimated by calculating residuals of in situ density from its large‐scale (filter window size ∼560 km) background and normalizing the residual with the background, as has been commonly used in terrestrial aeronomy. The disturbances are statistically stronger (a) in the local winter hemisphere than in summer and (b) on the nightside than on the dayside, with stark contrast across the terminator. The disturbances are more intense over the regions with strong radial magnetic fields (i.e., Martian crustal anomaly) than at unmagnetized regions, especially during the nighttime. Day‐to‐day variability of the Martian ionospheric disturbances does not exhibit a strong correlation with those of thermospheric CO2 disturbances or solar wind electron density/temperature at Mars.

A Parabolic Waveform Generator Based on the Chirp Characteristics of a Directly Modulated Laser

Due to carrier dynamics, the modulated light field from a directly modulated laser (DML) has an intensity envelope with a certain frequency chirp. When the chirp is linearly mapped into intensity by a frequency discriminator such as an optical filter with a linear edge, the optical field presents a new signal determined by the multiplication operation between the envelope function and the chirp function. Under a triangular drive signal, this process can contribute dark, bright and frequency-doubled bright parabolic waveforms by properly adjusting the filter window. This method is verified by both a theoretical analysis and experimental demonstrations. It not only provides a low-cost and simple scheme to generate parabola signals, but also a new method for arbitrary waveform generation.