Atrial fibrillation (AF) is the most common clinically significant arrhythmia; therefore, AF detection is crucial. Here, we propose a novel feature extraction method to improve AF detection performance using a ballistocardiogram (BCG), which is a wea...
The spatial distribution of night-time lights (NTL) provides a new perspective for studying the range and influence of human activities. However, most studies employing NTL time series are based on monthly or annual composite data, and time series st...
Functional near-infrared spectroscopy (fNIRS) is an effective non-invasive neuroimaging technique for measuring hemoglobin concentration in the cerebral cortex. Owing to the nature of fNIRS measurement principles, measured signals can be contaminated...
Long-term structural health monitoring (SHM) has become an important tool to ensure the safety of infrastructures. However, determining methods to extract valuable information from large amounts of data from SHM systems for effective identification o...
High-resolution measurement data from photovoltaic–building systems enable analyses that extend beyond static energy balances toward the temporal structure of system operation. This study proposes a window-based analytical pipeline to identify...
Background/Objectives: While intravenous thrombolysis (IVT) is the standard treatment for acute ischemic stroke (AIS) within 4.5 h of symptom onset, many patients present beyond this time window. Recent trials suggest that IVT may be both effective a...
Human monitoring systems are already utilized in various fields like assisted living, healthcare or sport and fitness. They are able to support in everyday life or act as a pre-warning system. We developed a system to monitor the ascent of a sport cl...
MODerate resolution Imaging Spectroradiometer (MODIS) data are largely used in multitemporal analysis of various Earth-related phenomena, such as vegetation phenology, land use/land cover change, deforestation monitoring, and time series analysis. In...
The hardware-accelerated time–frequency distribution calculation is one of the commonly used methods to analyze and present the information from intercepted radio frequency signals in modern ultra-wideband digital receiver (DRX) designs. In thi...
The products of a batch process have high economic value. Meanwhile, a batch process involves complex chemicals and equipment. The variability of its operation leads to a high failure rate. Therefore, early fault diagnosis of batch processes is of gr...
Modal parameters can reflect the dynamic characteristics of the structure and can be used to control vibration. To identify the operational modal parameters of linear slow-time-varying structures only from non-stationary vibration response signals, a...
The traditional sequential pattern mining method is carried out considering the whole time period and often ignores the sequential patterns that only occur in local time windows, as well as possible periodicity. Therefore, in order to overcome the li...
Understanding the underlying processes and extracting detailed characteristics of rivers is critical and has not yet been fully developed. The purpose of this study was to examine the performance of non-linear time series methods on environmental dat...
We extend the classical fractal uncertainty principle (FUP) framework in time-frequency analysis by exploring several novel directions. First, we generalize the FUP beyond the classical Gaussian window by investigating non-Gaussian windows and the co...
This article presents a method for extracting neural signal features to identify the imagination of left- and right-hand grasping movements. A functional magnetic resonance imaging (fMRI) experiment is employed to identify four brain regions with sig...
Uncertainty analysis is considered to be a necessary step in the process of vessel traffic risk assessment. The purpose of this study is to propose the uncertainty analysis algorithm which can be used to investigate the reliability of the risk assess...
In this study, we systematically investigate a road-rail intermodal routing problem the optimization of which is oriented on the customer demands on transportation economy, timeliness and reliability. The road-rail intermodal transportation system is...
The identification of critical fault information plays a crucial role in ensuring the reliability and stability of power systems. However, existing fault-identification technologies heavily rely on high-dimensional sensor data, which often contain re...
Electromyogram (EMG)-based Pattern Recognition (PR) systems for upper-limb prosthesis control provide promising ways to enable an intuitive control of the prostheses with multiple degrees of freedom and fast reaction times. However, the lack of robus...
In this paper, we propose an instantaneous chirp-rate-driven adaptive window Chirplet transform algorithm for the analysis of strong time-varying nonlinear frequency-modulated signals with uncorrelated components. In this approach, the length of the...
In view of the high false alarm rate in the oil debris monitoring results of the triple-coil inductive sensor in the transmission lubrication system of the aero-engine, a new debris signal processing method based on inductive monitoring is proposed....
In Vietnam, foreign direct investment (FDI) is an important capital flow for sustainable socio-economic growth and international economic integration, contributing to the supplementation of capital, modern technology, management and business capacity...
An uncertainty analysis is required to be carried out in formal safety assessment (FSA) by the International Maritime Organization. The purpose of this article is to introduce the uncertainty analysis technique into the FSA process. Based on the unce...
Outliers are observations suspected of not having been generated by the underlying process of the remaining data. Many applications require a way of identifying interesting or unusual patterns in multivariate time series (MTS), now ubiquitous in many...
Vegetation monitoring and mapping based on multi-temporal imagery has recently received much attention due to the plethora of medium-high spatial resolution satellites and the improved classification accuracies attained compared to uni-temporal appro...
Automated quality control could have a substantial economic impact on the dairy industry. At present, monitoring of yogurt production is performed by sampling for microbiological and physicochemical measurements. In this study, Near-Infrared Spectros...
Water stock monitoring is a major issue for society on a local and global scale. Sentinel-1&2 satellites provide frequent acquisitions to track water surface dynamics, proxy variables to enable water surface volume monitoring. How do we combine s...
Time-restricted eating (TRE) is a circadian rhythm-based intermittent fasting intervention that has been used to treat obesity. However, the efficacy and safety of TRE for fat loss have not been comprehensively examined and the influences of TRE char...
After peripheral nerve injury, axon and myelin regeneration are key events for optimal clinical improvements. We have previously shown that early bone marrow mononuclear cell (BMMC) transplantation exerts beneficial effects on myelin regeneration. In...
Neuroblastoma (NB) is a tumor of the developing sympathetic nervous system. Despite recent advances in understanding the complexity of NB, the mechanisms that determine its regression or progression are still largely unknown. Stage 4S NB is character...
The increasing incorporation of power electronics and other non-linear loads, in addition to their energy advantages, also implies a poor power quality, especially as regards harmonic pollution. Different solutions have been proposed to measure harmo...
The NP-hard coordination of heterogeneous robots for time-windowed warehouse tasks remains challenging: metaheuristics are precise but slow, whereas neural methods cannot handle heterogeneous constraints, leading to infeasible allocations. This paper...
The safe and efficient navigation of ships traversing the Northern Sea Route demands accurate information regarding sea ice concentration. However, the sea ice concentration forecasts employed to support such navigation are often flawed. To address t...
This paper introduces the prototype of a generic fuzzy algebraic framework, that aims to serve as a holistic modeling approach of kinematics. Moreover, it detects paradoxes and uncertainties when the involved features of the timeseries have “un...
Among the invertible orthogonal transforms employed to perform the analysis and synthesis of 2D signals (especially images), the ones defined by means of John von Neumann’s cardinal sinus are extremely interesting. Their definitions rely on tra...
Accurate energy consumption forecasting is essential for efficient power grid management, yet existing deep learning models struggle with the multi-scale nature of energy consumption patterns. Contemporary approaches like LSTM and GRU networks proces...
Accumulation of toxic metals in infants/children is of serious concern worldwide, from the viewpoint of their harmful effects on the normal growth and development. This metallomics study investigates the extent of toxic metal burdens in infants/child...
Identifying inflow and infiltration (I/I) in urban sewer networks is challenging due to nonlinear hydraulic interactions and time-lag effects between river stages and pipeline water levels. This study proposes a multi-scale fusion correlation model i...
Although lake surface water temperature (LSWT) is defined as an essential climate variable (ECV) within the global climate observing system (GCOS), current satellite-based retrieval techniques do not fulfill the GCOS accuracy requirements. The split-...
The research problem addressed in this paper concerns the formulation of feasibility conditions for planned service missions in networks where fulfilling customer orders requires the coordinated participation of multiple resources—referred to a...
Reliable estimation of the air change rate from CO2 decay measurements is essential for ventilation assessment, but results may strongly depend on the assumed background concentration and the selected analysis window. This study compares the ISO 1256...
Wastewater treatment plants (WWTPs) face two fundamental challenges: on the one hand, they must ensure an efficient application of preventive maintenance plans for their survival under competitive environments; and on the other hand, they must simult...
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...
High performance liquid chromatography method with ultra-violet detection (HPLC-UV) fingerprinting was applied for the analysis and characterization of olive oils, and was performed using a Zorbax Eclipse XDB-C8 reversed-phase column under gradient e...
Hydration level (HL) is a critical physiological indicator of human health and functional status, and accurate HL monitoring is essential for applications in healthcare, sports, and wellness assessment. However, existing methods are either invasive a...
Background: Understanding the physical demands of basketball at different competitive levels is essential for optimizing training and performance. While elite players are often assumed to experience the highest physical loads, evidence comparing peak...
S5 0716+714 is a well known BL Lac object, and one of the brightest and most active blazars. The discovery in the Very High Energy band (VHE, E > 100 GeV) by MAGIC happened in 2008. In January 2015, the source went through the brightest optical st...
Forecasting the dynamics of the number of cases with coronavirus disease 2019 (COVID-19) in a given population is a challenging task due to behavioural changes which occur over short periods. Planning of hospital resources and containment measures in...
Intelligent transportation systems increasingly rely on electric vehicle fleets operating under uncertain conditions, where routing decisions must adapt to changes in customer demand, service duration, and travel time while satisfying battery, chargi...
In the mining industry, where equipment breakdowns cause expensive unplanned downtime, operational continuity is paramount. Internet of Things (IoT) technologies have the potential to make predictions; however, most solutions lack a holistic view and...
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