Time series of Global Positioning System (GPS) station positions include signals whose characteristics vary over time. Therefore, in detailed analyses, methods dedicated to nonstationary time series should be used. In this study, the Complementary En...
Time series classification (TSC) is always a very important research topic in many real-world application domains. MultiRocket has been shown to be an efficient approach for TSC, by adding multiple pooling operators and a first-order difference trans...
Noises in the GPS vertical coordinate time series, mainly including the white and flicker noise, have been proven to impair the accuracy and reliability of GPS products. Various methods were adopted to weaken the white and flicker noises in the GPS t...
Crude oil is one of the main energy sources and its prices have gained increasing attention due to its important role in the world economy. Accurate prediction of crude oil prices is an important issue not only for ordinary investors, but also for th...
Let
Economic diversification remains a central policy challenge for small, sectorally concentrated jurisdictions. This paper examines whether jurisdiction-level ESG conditions and fiscal-revenue outcomes are individually and jointly associated with growt...
It is crucial to predict landslide displacement accurately for establishing a reliable early warning system. Such a requirement is more urgent for landslides in the reservoir area. The main reason is that an inaccurate prediction can lead to riverine...
By examining Fourier–Legendre series pairs
Structural breaks and volatility clustering are fundamental challenges in time series analysis. We propose CQEformer, an encoder-only Transformer variant for time-series modeling that addresses these challenges via two complementary innovations. Firs...
Time series forecasting serves a critical function in domains such as energy, meteorology, and power systems by leveraging historical data to predict future trends. However, existing methods often prioritize long-term dependencies while neglecting th...
Modern distribution networks face growing challenges from demand growth, electrification, and distributed energy resources, complicating voltage regulation and service quality. While demand response has been proposed as a complementary tool, most exi...
This study reports 12 cases of inaccurate bone cutting from a single-surgeon series of 509 consecutively performed robotic-assisted total knee arthroplasty (TKA) for 1 year. In addition, a complementary technique with the combined benefits of robotic...
Dead time between the complementary driving signals is needed to avoid short circuit in voltage source inverters (VSIs), however, this raises issues such as voltage distortion and harmonic generation. In wireless power transfer (WPT) systems, the rat...
The increasing availability of time series datasets enabled by the diffusion of IoT architectures and the progress in the analysis of temporal data fostered by Deep Learning methods are boosting the interest in anomaly detection and predictive mainte...
We present a multiscale analysis of the price dynamics of U.S. sector exchange-traded funds (ETFs). Our methodology features a multiscale noise-assisted approach, called the complementary ensemble empirical mode decomposition (CEEMD), that decomposes...
Time-delayed interactions naturally appear in a multitude of real-world systems due to the finite propagation speed of physical quantities. Often, the time scales of the interactions are unknown to an external observer and need to be inferred from ti...
The monitoring of perennial and annual crops requires different analytical approaches due to their contrasting phenological dynamics and management practices. This study investigates the temporal behavior of the Normalized Difference Vegetation Index...
Structural break tests for regression models are sensitive to model misspecification. We show—analytically and through simulations—that the sup Wald test for breaks in the conditional mean and variance of a time series process exhibits se...
Both the stretched exponential function and the Prony series are prominent mathematical frameworks extensively employed to characterize monotonically decaying phenomena across physics and engineering disciplines. Despite being fundamentally distinct...
In this paper, complementary metamaterial sensor is designed for nondestructive evaluation of dielectric substrates. The design concept is based on electromagnetic stored energy in the complementary circular spiral resonator (CCSR), which is concentr...
Online monitoring systems continuously collect massive multivariate time-series data from converter transformers. Accurate outlier detection in these data is essential for identifying sensor faults, communication errors, and incipient equipment failu...
Aiming at the problems of existing time series data clustering methods, such as the lack of similarity metric universality, the influence of dimensional catastrophe, and the limitation of feature expression ability, a time series data clustering meth...
Time irreversibility, i.e., the lack of invariance of a system under the operation of time reversal, has long attracted the attention of the statistical physics community, and has been shown to be a relevant marker of altered dynamics in many real-wo...
Mid-deep geothermal heat pump systems (MD-GHPs) feature high energy efficiency and low energy consumption, yet their promotion is restricted by high initial investment. While the initial investment of air-source heat pumps (ASHPs) is obviously lower,...
In recent years, although deep learning algorithms have been widely applied to various fields, ranging from translation to time series forecasting, researchers paid limited attention to modelling parameter optimization and the combination of the fuzz...
Identifying acetylcholinesterase (AChE) ligands for Alzheimer’s disease research requires integrating molecular recognition with pharmacokinetic and safety considerations. Here, four designed chromone derivatives (M1–M4) were investigated...
Background: Although dietary fat and carbohydrates are major determinants of gut microbiota composition, their interactive effects across changing dietary monosaccharide-to-lard energy ratios remain incompletely understood. This study descriptively e...
Several 2-substituted (H, Ph, and S-Me) and 1-substituted (H, Ph, and Bn), 3-hydroxy-1,3-quinazolin(di)ones were utilized for the first time as radical trapping agents in asymmetric 1,2-oxytrifluoromethylation of styrenes catalyzed by chiral vanadyl...
Small airway dysfunction (SAD) is an early functional abnormality associated with multiple chronic airway diseases. However, clinical assessment often relies on spirometry-based indices, which require forced maneuvers and are sensitive to subject eff...
Carbohydrate-derived isothiocyanates are attractive glycomimetic redox modulators because the sugar scaffold can tune the chemical environment of the electrophilic N=C=S group. Two complementary families of S-glycosyl isothiocyanates bearing the ITC...
Background: Many efforts are made to find safer and more feasible therapeutic strategies to improve gynaecological care. Non-pharmacological treatments, such as osteopathic interventions, could be used as complementary strategies to better manage dif...
Corporate resilience has become a critical capability for firms to cope with increasing environmental uncertainties and external shocks. Against the backdrop of the rapid development of the digital economy, this study examines whether digital transfo...
At present, the global carbon neutrality action is intended to change the energy structure and promote the development of regional energy trade, which is conducive to alleviating the contradiction between energy supply and demand. Based on this, the...
Background: Pediatric lymphadenopathy is a common reason for consultation, but information from secondary-level care in Latin American middle-income settings remains limited. Objective: The objective of this study is to describe the clinical profile,...
The standardized precipitation index (SPI) provides reliable estimations about the intensity, magnitude and spatial extent of droughts in a variety of time scales based on long-term precipitation series. In this work, we assess the evolution of month...
Producer share indicators summarize how value is distributed along agrifood supply chains, yet their temporal dynamics remain difficult to compare across products and periods. This paper proposes a reproducible time-series analytics framework to char...
In an ongoing series of spotlight interviews, Challenges Advisory Board Member and Nova Institute for Health Fellow, Alan C. Logan, meets with thought leaders, scientists, scholars, healthcare professionals, artisans and visionaries concerned about h...
The assessment of time irreversibility, i.e., of the lack of invariance of the statistical properties of a system under the operation of time reversal, is a topic steadily gaining attention within the research community. Irreversible dynamics have be...
Ionic liquids (ILs) have been explored as a surface modification strategy to promote the oxygen reduction reaction (ORR) on Pt/C and their chemical structures were identified to have strong influence on the ORR activities. To better understand the ro...
Solar magnetic activity exhibits a complex nonlinear behavior, but its dynamic process has not been fully understood. As the complex network technique can better capture the dynamics of nonlinear system, the visibility graphs (VG), the horizontal vis...
In this paper, a novel voltage equalizer is developed for series battery strings based on the two-phase switched capacitor technique. Different from the conventional voltage equalizers which are developed by switched-mode power converters, bulky magn...
Time-series forecasting is a cornerstone of decision making in domains such as finance, energy management, and meteorology, where precise predictions drive both economic and operational efficiency. However, traditional time-domain methods often strug...
Distinguishingstructured nonlinear temporal behaviour from stochastic variability remains a fundamental challenge in the analysis of noisy and nonstationary time series, particularly when conventional nonlinear methods are sensitive to noise and fini...
Auditory brainstem response (ABR) threshold determination requires clinicians to identify the transition between waveforms with and without a detectable response across stimulus intensities. Automation remains challenging because responses near the t...
Determining the sea surface height using Global Navigation Satellite System (GNSS) buoys is an important method for satellite altimetry calibration. The buoys observe the absolute height of the sea surface using GNSS positioning technology, which is...
Accurate land-cover mapping in tropical regions remains challenging because of high environmental heterogeneity, complex vegetation structure, and persistent cloud cover. Recent geospatial foundation models provide pre-computed Geo-embeddings that of...
Distributed renewable energy sources with significant output fluctuations can negatively impact the power grid stability when it is connected to the power grid. Therefore, it is necessary to develop a capacity configuration method that improves the o...
Recent developments in satellite data availability allow tropical forest monitoring to expand in two ways: (1) dense time series foster the development of new methods for mapping and monitoring dry tropical forests and (2) the combination of optical...
Cardiovascular deterioration is a clinically important event in intensive care units, but early prediction remains challenging because risk may be reflected across structured clinical variables, physiological time series, and clinical text. In this w...
Extropy, the complementary dual of Shannon entropy, has Rényi and Tsallis generalizations. For finite discrete distributions, a general asymptotic theory for plug-in estimators of functionals
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