78 Results Found

Sample entropy, an approximation of the Kolmogorov entropy, was proposed to characterize complexity of a time series, which is essentially defined as $-log(B/A)$, where B denotes the number of matched template pairs with length m and A denotes th...

Entropy is one of the most fundamental notions for understanding complexity. Among all the methods to calculate the entropy, sample entropy (SampEn) is a practical and common method to estimate time-series complexity. Unfortunately, SampEn is a time-...

Approximate Entropy and especially Sample Entropy are recently frequently used algorithms for calculating the measure of complexity of a time series. A lesser known fact is that there are also accelerated modifications of these two algorithms, namely...

Many popular entropy definitions for signals, including approximate and sample entropy, are based on the idea of embedding the time series into an m-dimensional space, aiming to detect complex, deeper and more informative relationships among samples....

This paper introduces a new method of estimating Shannon entropy. The proposed method can be successfully used for large data samples and enables fast computations to rank the data samples according to their Shannon entropy. Original definitions of p...

This study evaluates four databases from PhysioNet: The American Heart Association database (AHADB), Creighton University Ventricular Tachyarrhythmia database (CUDB), MIT-BIH Arrhythmia database (MITDB), and MIT-BIH Noise Stress Test database (NSTDB)...

The two-dimensional sample entropy marks a significant advance in evaluating the regularity and predictability of images in the information domain. Unlike the direct computation of sample entropy, which incurs a time complexity of $O\left(N^2\right)$ for the serie...

Sample Entropy is the most popular definition of entropy and is widely used as a measure of the regularity/complexity of a time series. On the other hand, it is a computationally expensive method which may require a large amount of time when used in...

Relative consistency is a notion related to entropic parameters, most notably to Approximate Entropy and Sample Entropy. It is a central characteristic assumed for e.g., biomedical and economic time series, since it allows the comparison between diff...

In this paper, a fetal electrocardiogram (ECG) monitoring system based on the Android smartphone was proposed. We designed a portable low-power fetal ECG collector, which collected maternal abdominal ECG signals in real time. The ECG data were sent t...

To improve the fault identification accuracy of rolling bearing and effectively analyze the fault severity, a novel rolling bearing fault diagnosis and severity analysis method based on the fast sample entropy, the wavelet packet energy entropy, and...

In this study, a multistage segmentation technique is proposed that identifies cancerous cells in prostate tissue samples. The benign areas of the tissue are distinguished from the cancerous regions using the texture of glands. The texture is modeled...

With the development of the carbon market in China, research on the carbon price has received more and more attention in related fields. However, due to its nonlinearity and instability, the carbon price is undoubtedly difficult to predict using a si...

The evaluation of complexity in univariate signals has attracted considerable attention in recent years. This is often done using the framework of Multiscale Entropy, which entails two basic steps: coarse-graining to consider multiple temporal scales...

Popcoen is a method for configurational entropy estimation of proteins based on machine-learning. Entropy is predicted with an artificial neural network which was trained on simulation trajectories of a large set of representative proteins. Popcoen i...

Entropy-based complexity of cardiovascular variability at short time scales is largely dependent on the noise and/or action of neural circuits operating at high frequencies. This study proposes a technique for canceling fast variations from cardiovas...

The discrimination of non-focal class (NFC) and focal class (FC), is vital in localizing the epileptogenic zone (EZ) during neurosurgery. In the conventional diagnosis method, the neurologist has to visually examine the long hour electroencephalogram...

Dispersion entropy (DispEn) is a recently introduced entropy metric to quantify the uncertainty of time series. It is fast and, so far, it has demonstrated very good performance in the characterisation of time series. It includes a mapping step, but...

In this paper, we present a novel approach for the optimal camera selection in video games. The new approach explores the use of information theoretic metrics f-divergences, to measure the correlation between the objects as viewed in camera frustum a...

Speckle is an interference phenomenon that contaminates images captured by coherent illumination systems. Due to its multiplicative and non-Gaussian nature, it is challenging to eliminate. The non-local means approach to noise reduction has proven fl...

Sentiment analysis is essential for understanding consumer opinions, yet selecting the optimal models and embedding methods remains challenging, especially when handling ambiguous expressions, slang, or mismatched sentiment–rating pairs. This s...

The discrimination of early Alzheimer’s disease (AD) and its prodromal form (i.e., mild cognitive impairment, MCI) from cognitively healthy control (HC) subjects is crucial since the treatment is more effective in the first stages of the dementia. Th...

To mitigate the high measurement costs in electromagnetic compatibility (EMC) assessment, this paper proposes a robust active learning framework for fast 3D field reconstruction with sparse sampling. A novel “Four-Vote” query criterion is...

In-situ TEM-heating study of the microstructural evolution of CrFeCoNiCu high entropy alloy (HEA) thin films was carried out and morphological and phase changes were recorded. Post annealing investigation of the samples was carried out by high resolu...

The amorphous AlTiCrFeMoSi high entropy alloy (HEA) coating with high hardness (11.88 GPa) is successfully deposited on T91 substrate by the magnetron sputtering method. Both T91 steel and as−deposited AlTiCrFeMoSi coating samples are exposed t...

In this paper, based on integer-order Hindmarsh–Rose (HR) neurons under an electric field, the fractional-order model is constructed, and the nonlinear term is decomposed by the Adomian decomposition method, and the numerical solution of the sy...

Rolling bearings, as critical components of rotating machinery, significantly influence equipment reliability and operational efficiency. Accurate fault diagnosis is therefore crucial for maintaining industrial production safety and continuity. This...

Deep learning models excel in interpreting the exponentially growing amounts of remote sensing data; however, they are susceptible to deception and spoofing by adversarial samples, posing catastrophic threats. The existing methods to combat adversari...

In order to achieve 0.1 m resolution and fully polarimetric observation capabilities for airborne SAR systems, the adoption of stepped-frequency modulation waveform combined with the polarization time-division transmit/receive (T/R) technique proves...

Refractory metals typically exhibit limited room temperature ductility, hampering their widespread application. Recent advances in refractory high-entropy alloys have focused on finding optimum combinations of strength and ductility but require explo...

In this paper a novel adaptive rapidly-exploring random trees algorithm based on cross-entropy optimization (CE-RRT) is proposed. We seek to provide a low-cost, fast, and effective solution for path planning of robots in various complex environments....

In this study, the removal of nickel (Ni(II)) by adsorption from synthetically prepared solutions using natural bentonites (Lieskovec (L), Hliník nad Hronom (S), Jelšový Potok (JP), and Stará Kremnička (SK)) was investigat...

Latent heat thermal energy storage (LHTES) systems based on phase change materials (PCMs) are central to improving energy efficiency in solar–thermal, waste-heat recovery, and building energy management applications; however, minimizing the the...

Electrohysterography (EHG) has been shown to provide relevant information on uterine activity and could be used for predicting preterm labor and identifying other maternal fetal risks. The extraction of high-quality robust features is a key factor in...

Biosensors and immunosensors show an increasing attractiveness when developing current cheap and fast monitoring and detecting devices. In this work, a model of immunosensor in a class of delayed lattice differential equations is offered and studied....

Methods of machine learning and data mining are becoming the cornerstone in information technologies with real-time image and video recognition methods getting more and more attention. While computational system architectures are getting larger and m...

A short-term power load forecasting method is proposed based on an improved Sparrow Search Algorithm (ISSA), Variational Mode Decomposition (VMD), and Bidirectional Long Short Term Memory (BiLSTM) neural network. First, the SSA is optimized by combin...

Numerous novel improved support vector machine (SVM) methods are used in leak detection of water pipelines at present. The least square twin K-class support vector machine (LST-KSVC) is a novel simple and fast multi-classification method. However, LS...

We present a novel nonparametric adaptive partitioning and stitching (NAPS) algorithm to estimate a probability density function (PDF) of a single variable. Sampled data is partitioned into blocks using a branching tree algorithm that minimizes devia...

This block-randomized crossover study investigated how a speed-modulated aquatic treadmill (AT) impacts the walking biomechanics of pediatric gait. Eight cerebral palsy (CP) and fifteen typically developing (TD) children walked at normal, slow, and f...

Since path planning for multi-arm manipulators is a complicated high-dimensional problem, effective and fast path generation is not easy for the arbitrarily given start and goal locations of the end effector. Especially, when it comes to deep reinfor...

With the rise in physiological data sampled from wearable devices, efficient methods must be developed to encode temporal information for the comparison of time series arising from uncontrolled monitoring. We present a fast, nonparametric method call...

Accurate and fast transient stability assessment (TSA) of power systems is crucial for safe operation. However, deep learning-based methods require long training and fail to simultaneously extract the spatiotemporal characteristics of the transient p...

Salt crystallization represents one of the primary forms of weathering encountered in rock cultural heritage sites, with sulfate weathering having particularly notable destructive effects. This study focuses on sandstone and limestone, using them as...

The integration of large-scale renewable energy sources has increased the complexity of operation and maintenance in modern power systems, causing on-site substation operation and maintenance activities to exhibit stronger continuity and dynamics, an...

Improving the processability of ultrahigh molecular weight polyethylene (UHMWPE) and understanding the effect of the polymeric chain mobility has long been a challenging task. Herein, we show that UHMWPE without any processing aids can be processed a...

The study of nonlinear and possibly chaotic time-dependent systems involves long-term data acquisition or high sample rates. The resulting big data is valuable in order to provide useful insights into long-term dynamics. However, efficient and robust...

Compared with the amplitude modulation of conventional interrupted sampling repeater jamming (ISRJ), the image feature control method based on phase modulation exhibits greater energy efficiency and, therefore, has received wide attention recently. I...

Magnetic Resonance Imaging (MRI) reconstruction is computationally heavy from under sampled data, and centralized data sharing within deep learning models was met with privacy concerns. We therefore propose FL-Swarm MRCM, a novel federated learning f...

In this paper we report the effect of three different preparation methods on the first hydrogenation of the vanadium-rich BCC alloy Ti₁₆V₆₀Cr₂₄: one-time cold rolling, 5 min ball milling and addition of 4 wt.% of Zr. All samples were synthesized by a...