Filtering - Science topic

This paper proposes a new technique designed to prevent and detect address resolution protocol (ARP) spoofing attacks in general, and specifically Man-in-the-Middle (MitM) attacks, within the context of cloud computing. The solution focuses on establishing appropriate flow filtering rules based on parameters such as 'time feature' and internet cont...

Multi-material topology optimization has become a promising method in structural design due to its excellent structural performance. However, existing research assumes that the multi-material structures are joined by welding, adhesive, or other methods that do not support reassembly and disassembly and are unsuitable for manufacturing, limiting the...

Maintaining a stable balance between generated power and load demand is a critical challenge in modern power systems, especially with the increasing integration of renewable energy sources like photovoltaic (PV) systems. This study introduces a novel hybrid educational competition optimizer with pattern search (hECO-PS) algorithm to optimally tune...

In wave energy systems, in contrast to other renewable energy applications, the external input acting on the system is not a measurable quantity. Simultaneously, knowledge of this wave excitation force is essential for the operation of energy-maximising controllers. Considering these aspects, the problem addressed in this paper is that of the desig...

This research addresses the critical challenge of broadband matching in radio engineering, focusing on enhancing phase-frequency response (PFC) linearity across wide frequency bands. A novel approach, utilizing modified Chebyshev functions, demonstrates significant potential in reducing phase distortions within 5G technology applications. Unlike tr...

In the realm of synchronization techniques, the dichotomy between open loops (OLSs) and closed loops (CLSs) presents a perennial challenge: how to enhance dynamic performance without sacrificing stability and disturbance rejection. While OLS techniques offer rapid dynamic response and unwavering stability, they often falter in non-nominal frequency...

This paper introduces a novel method for controlling shunt active power filters (SAPFs) to improve network efficiency and reduce carbon emissions in the utility sector. It addresses the problem of current harmonics degrading system performance by employing reference current generation based on the least mean square (LMS) algorithm, it decomposes di...

The development of new technologies has made image watermarking crucial in the digital era to preserve and protect illegal distribution of images against unauthorized users. This paper presents a robust image watermarking technique that employs a set of embedding rules in the three-level of integer wavelet transform (IWT). The proposed method aims...

The purpose of this article is to examine the economic cycles in Colombia and to empirically corroborate the fulfillment of nine stylized facts documented in the specialized international literature. For this purpose, the retropolated series 1975-2013 and the series 2005:1-2022:4 of the National Administrative Department of Statistics (DANE) were a...

Stabilization of optical beams has always been a key factor affecting the performance of many optical systems. The Adaptive optics (AO) beam stabilization system requires further development to cope with increasingly complex application scenarios and challenges. Motivated by this, a new filter-based off-policy policy iteration (FB-OPPI) control sch...

Due to the increasing use of power electronics equipment, the quality of energy in the electrical network is deteriorating sharply. Indeed, this equipment consumes non-sinusoidal currents, even if they are powered by a sinusoidal voltage, and behaves like generators of harmonic currents. To "clean up" the network, there are several means, among the...

Acquiring high-resolution light fields (LFs) is expensive. LF angular superresolution aims to synthesize the required number of views from a given sparse set of spatially high-resolution images. Existing methods struggle with sparsely sampled LFs captured with large baselines. Some methods rely on depth estimation and view reprojection, and are sen...

For fractional order systems with colored process noise, the discretization fractional order system model is used to construct the augmented vector defined by the state vector and colored process noise vector. Based on the augmented equation of fractional order systems, the robust local Kalman filtering algorithm for fractional order systems with c...

This study investigates trends in the issuance of FDA warning letters from 2019 to 2023. The paper aims to assess past and present FDA statements of inspection efficiency from a quantitative and qualitative perspective. An analytical approach combining regex filtering and web scraping was developed to log citations of law within FDA warning letters...

Noise prewhitening converts nonwhite noise in noisy speech into white noise, a preprocessing step to improve the performance of subsequent processing tasks. This is done by estimating and flattening the power spectral density (PSD) of noise. However, accurate estimation of PSD can be challenging, especially when dealing with nonstationary noise. We...

This work shows the design and validation of a Shunt Active Power Filters (SAPF) using Controller Hardware-In-the-Loop (CHIL) Simulations by using a OP5707XG Real-Time Simulator module provided by OPAL-RT, an external OP8666 controller, a host PC and an oscilloscope for visualization. A novel methodology for the modelling of real non-linear electri...

In this paper, improvement of power quality (PQ) in a distribution system using a PV-series active power filter (PV-SAPF) investigated. The performance of the proposed filter is increased using an enhanced Jaya optimized proportional integral (PI) with indirect current controller (ICC) technique system. In existing Jaya optimization technique best...

In this paper, the cascade architecture of spline adaptive filtering (CSAF) for nonlinear systems is presented with the normalized version of orthogonal gradient adaptive (NOGA) algorithm. Spline adaptive filtering comprises a sandwich of the first linear adaptive filtering (LAF) and nonlinear adaptive look-up table. In this cascading architecture,...

Indirect-current-controlled active power filter (APF) is preferable compared with the direct-current-controlled APF due to its simpler structure and its direct regulation of the grid current. However, unlike direct current control, indirect current control does not have explicit current reference posing difficulty on current limiting operation. Thi...

The series hybrid active power filter (SHAPF) is known as a very effective harmonic filtering model in power systems. Typically, SHAPF is controlled by a control method based either on the harmonic voltage of the load or on the supply harmonic current. However, the above two methods have the disadvantage of requiring the control coefficient much be...

Piston error is the main component of the co-phase errors of segmented telescopes. In this paper, we innovatively performed frequency domain filtering and processing on the focal plane image of the segmented telescopes with mask added, and obtained the image that only reflects the piston error between each submirror and the reference submirror. The...

This paper introduces a LCL filter design tailored for a 40 kW three-phase grid-connected converter utilized in electric vehicle onboard fast chargers. In contrast to conventional filters, the LCL filter finds extensive application in AC/DC converters for power factor correction, thanks to its enhanced harmonic reduction and improved stability of t...

Purpose: The deep learning time-of-flight (DL-ToF) aims to replicate the ToF effects through post-processing, applying deep learning-based enhancement to PET images. This study evaluates the effectiveness of DL-ToF using a chest-abdomen phantom that simulates human anatomical structures. Methods: The 3 DL-ToF intensities (Low-DL-ToF: LDL, Middle-DL...

Today, the increase in the number of devices working based on speech interfaces increases the importance of speech quality. However, even a minimal noise level can seriously affect the accuracy of speech signal recognition and processing. Therefore, denoising speech signals is an important task in signal processing, and it also serves to improve sp...

1. Gambaran Umum Buku ini membahas bagaimana konsep imagined communities yang diperkenalkan oleh Benedict Anderson dalam konteks nasionalisme dapat diterapkan pada dunia siber. Dr. Sulianta mengeksplorasi transformasi media cetak menjadi media digital, menciptakan komunitas yang melampaui batas fisik dan geografis. Buku ini relevan dengan dunia tek...

Gambaran Umum Buku Imagined Community Dunia Siber karya Dr. Feri Sulianta mengeksplorasi bagaimana konsep "komunitas terbayang" yang diperkenalkan oleh Benedict Anderson dalam konteks nasionalisme berevolusi di era digital. Anderson berargumen bahwa bangsa adalah komunitas yang "dibayangkan" oleh anggotanya melalui media, seperti surat kabar dan bu...

Breast cancer begins in the breast tissues and can progressively spread to other parts of the body. Early detection is crucial, as it allows for timely treatment, potentially saving lives. Researchers have devised methods to detect cancer in its early stages. However, the majority of the approaches primarily utilize either attention-based deep mode...

Disease diagnosis tasks using microbial data are often hindered by extreme class imbalance issues, which are further manifested as inter-class and intra-class imbalances. The former can be handled by general methods such as the SMOTE, while the latter has not been well studied. In this paper, we propose an ensemble classification algorithm based on...

Environmental filtering and dispersal history limit plant distributions and affect biogeographical patterns, but how their relative importance varies across evolutionary timescales is unresolved. Phylogenetic beta diversity quantifies dissimilarity in evolutionary relatedness among assemblages and might help resolve the ecological and biogeographic...

The traditional multiple signal classification (MUSIC) algorithm is only suitable for narrowband array signals, however for wideband signals, sub-band division is required, most of which are based on preset filters or time–frequency analysis. These methods usually require manual selection of the parameters of the filters, basis functions, etc., acc...

Similar to the Web of Science, Scopus is also a widely used abstract and citation database. Researchers typically employ the Year of Publication or Date of Publication field in Scopus to retrieve, filter and analyse indexed records. However, the inconsistent retrieval results obtained by these two fields in Scopus, which was occasionally observed i...

This paper presents several machine learning methods and highlights the most effective one for detecting elephant rumbles in infrasonic seismic signals. The design and implementation of electronic circuitry to amplify, filter, and digitize the seismic signals captured through geophones are presented. The process converts seismic rumbles to a spectr...

Action evaluation can automatically detect abnormal actions by evaluating the quality of human actions in specific postures, which is widely used in the field of rehabilitation medicine. This paper proposes an intelligent rehabilitation action evaluation system to evaluate the quality of patients’ actions during rehabilitation training, which helps...

This paper introduces FEMemAE-Jigsaw, a hybrid detection framework that leverages a fusion of reconstruction and jigsaw puzzle detection for video anomaly detection. Initially, we developed a new reconstruction model, FEMemAE, which utilizes an expanded memory module to more effectively retain the original input data’s information. By incorporating...

Four innovative teaching-learning methods are implemented. First: learning by demonstration, second-solving GATE problem in laboratory, third-use of Game, fourth-use of case study. First experiment uses LM339 in place of MAX 998. In GATE problem solving, assumptions are essential with verification of numerical answer. In Fourier series game, learne...

The inherently high-dimensional and information-dense nature of point clouds requires substantial storage and computing resources, which severely limits their widespread applicability. It is crucial to simplify the point cloud data efficiently and accurately for various downstream tasks. To address the challenges of detail loss and time consumption...

Saliency object detection has been widely used in computer vision tasks such as image understanding, semantic segmentation, and target tracking by mimicking the human visual perceptual system to find the most visually appealing object. The U2Net model has shown good performance in salient object detection (SOD) because of its unique U-shaped residu...

This paper presents a comprehensive review of recommendation algorithms in the music domain. Music recommendation systems play a crucial role in delivering personalized content to users by analyzing patterns and preferences. We analyze several prominent recommendation algorithms, including collaborative filtering, content-based filtering, and hybri...

Microwave wireless power transmission (MWPT) applications have attracted worldwide interest and attention in recent years. Rectennas are a crucial component of a MWPT system. The rectenna’s power capacity and output DC power have great significance with regard to the MWPT system’s performance. In this article, a compact 4 × 4 S-band rectangular pat...

The aim of this study is to contribute to the theoretical studies on soft closed graphs and soft continuous mappings. We give a characterization of soft continuity using soft points and obtain a sufficient condition for the soft equalizer to be soft closed. We also present the notion of a soft filter generated by the soft net and vice-versa and pro...

Wavefront coding technique has been used to extend the depth of focus in an optical imaging system. An optical element called a phase mask allows coded images to be obtained since the point spread function remains almost invariant in an axial range. Subsequently, a computational technique is required to decode the acquired images. An optical-comput...

Closed-loop neuromodulation, especially using the phase of the electroencephalography (EEG) rhythm to assess the real-time brain state and optimize the brain stimulation process, is becoming a hot research topic. Because the EEG signal is non-stationary, the commonly used EEG phase-based prediction methods have large variances, which may reduce the...

Semantic surgical scene segmentation is crucial for accurately identifying and delineating different tissue types during surgery, enhancing outcomes and reducing complications. Hyperspectral imaging provides detailed information beyond visible color filters, offering an enhanced view of tissue characteristics. Combined with machine learning, it sup...

Plant organisms absorb heavy metals and pollutants from the atmosphere and are actively used in phytoremediation methods, being in fact a “filter” of ecosystems. Coniferous pine needles are one of the most frequently used objects of monitoring studies, which is due to a wide ecological amplitude and increased sensitivity to anthropogenic changes in...

Structured illumination microscopy (SIM) has attracted much attention from researchers due to its high accuracy, high efficiency, and strong adaptability. In SIM, demodulation is a key point to recovering three-dimensional topography, which directly affects the accuracy and validity of measurement. The traditional demodulation methods are the phase...

This paper studies a method to improve the accuracy of a deep learning model for detecting brain abnormalities based on computed tomography images. The process begins with image preprocessing using the Histogram Equation algorithm and Gabor filter. Then, features are extracted from the fully connected layer of the AlexNet model. To optimize feature...

En este artículo se introduce la teoría y el análisis de datos de ondas gravitacionales con el propósito de replicar, paso por paso, la detección y estimación de parámetros de la primera señal de onda gravitacional reportada por la colaboración LIGO. Para ello se presenta la teoría de Einstein linealizada, el desarrollo analítico de señales de sist...

Recommendation systems have been developed to address the immense volume of information accessible on the Internet. These systems employ filtering methodologies and customize their recommendations by drawing insights from user profiles, ultimately enhancing the relevance and utility of their suggestions. In this paper, we present our system called...

This paper investigates a rapid dynamical pattern modeling method for a class of nonlinear sampled-data systems. Firstly, within the nonlinear sampled-data systems framework, the consistency condition is presented based on the approximate discrete-time model. Then, a regression filter-based dynamic learning method is proposed to enhance online lear...

As an important part of intelligent traffic, vehicle recognition plays an irreplaceable role in traffic management. Due to the complexity and occlusion of various objects in the traffic scene, the accuracy of vehicle target recognition is poor. Therefore, based on the distribution features of vehicle components, this paper proposes a two-stage VSRS...

Current safety helmet detection models face challenges in terms of computational complexity and hardware requirements, particularly in resource-constrained environments like underground mines. To address these issues, we propose the BLP-YOLOv10 model, which optimizes feature extraction and image processing by adjusting backbone channel parameters,...

Contrastive Learning (CL) has recently achieved remarkable performance in recommendation systems, especially in Graph Collaborative Filtering (GCF), due to its effective handling of data sparsity issues by comparing positive and negative sample pairs. In CL-based GCF models, those sample pairs can be created by various data augmentation methods, wh...

High vibration poses significant safety and operational risks to compressor components. This study presents a thorough investigation of the root causes analysis and corrective actions to resolve vibration-induced failures faced on the suction system of a reciprocating compressor. Excessive pressure pulsations in the suction bottle and strong mechan...

The system of nonlinear tensor equations with Einstein product which is the generalized form of a system of nonlinear matrix equations studied in the literature, occurs in many applications such as network systems, filtering, control theory, and optimal control. In this study, first, we present a family of iterative methods avoid tensor inversion t...

Ambiguous words are often found in modern digital communications. Lexical ambiguity challenges traditional Word Sense Disambiguation (WSD) methods, due to limited data. Consequently, the efficiency of translation, information retrieval, and question-answering systems is hindered by these limitations. This study investigates the use of Large Languag...

The Lobo reservoir, designed to supply water to the Daloa city population (central west of Côte d’Ivoire), is facing the phenomenon of eutrophication due to the agricultural plots located upstream of the reservoir inputs. Studies have highlighted the reservoir pollution and sedimentation problems. This study was initiated to test the effectiveness...

Porous membranes are thin solid structures that allow the flow to pass through their tiny openings, called pores. Flow inertia may play a significant role in several filtration flows of natural and engineering interest. Here, we develop a predictive macroscopic model to describe solvent and solute flows past thin membranes for non-negligible inerti...

The impact of cognitive biases on decision-making in the digital world remains under-explored despite its well-documented effects in physical contexts. This paper addresses this gap by investigating the attractiveness halo effect using AI-based beauty filters. We conduct a large-scale online user study involving 2748 participants who rated facial i...

We present a novel class of Convolutional Neural Networks called Pre-defined Filter Convolutional Neural Networks (PFCNNs), where all nxn convolution kernels with n>1 are pre-defined and constant during training. It involves a special form of depthwise convolution operation called a Pre-defined Filter Module (PFM). In the channel-wise convolution p...

Unsupervised low-light image enhancement methods have gained attention and shown improvement with low data dependence. However, the lack of a ground truth presents challenges, notably in pronounced noise and color bias. This paper proposes a Self-Guided Pixel-wise Calibration method to overcome associated issues by leveraging inherent features from...

A PID controller design using an internal model control (IMC) approach is a well-established method for controller tuning in a DC-DC boost converter. This study introduces an innovative implementation of a novel indirect Internal Model Control (IMC) strategy for PID controller design, tailored specifically for a DC-DC boost converter. While the ind...

Motivation: Chest X-ray (CXR) is a routine diagnostic X-ray examination for checking and screening various diseases. Automatically localizing and classifying diseases from CXR as a detection task is of much significance for subsequent diagnosis and treatment. Due to the fact that samples of some diseases are difficult to acquire, CXR detection data...

Photoluminescent carbon dots (CDs) have received increasing attention because of their admirable photophysical performances. The current strategies for synthesizing CDs typically require high energy consumption levels, and the ability to synthesize CDs at ambient temperature would be highly desirable. Herein, we design an energy-efficient approach...

Marine snow, the floating particles in underwater images, severely degrades the visibility and performance of human and machine vision systems. This paper proposes a novel method to reduce the marine snow interference using deep learning techniques. We first synthesize realistic marine snow samples by training a Generative Adversarial Network (GAN)...

Computational analysis of whole slide images (WSIs) has seen significant research progress in recent years, with applications ranging across important diagnostic and prognostic tasks such as survival or cancer subtype prediction. Many state-of-the-art models process the entire slide - which may be as large as $150,000 \times 150,000$ pixels - as a...