Active vibration control is the most effective method for stochastic multidimensional vibration in wind tunnel tests, in which vibration monitoring is the core foundation. Vibrations are induced by the disturbances of several complex air flow instabi...
Within the field of permanent magnet synchronous motor sensorless speed control systems, we present a novel scheme with a Multi-dimensional Taylor Network (MTN)-based nonlinear observer as the core, supplemented by two auxiliary MTN modules to realiz...
We focus on the dual interval control problem of multidimensional objects with delay. We propose a new nonparametric algorithm. In such a case, it is not necessary to determine a parametric structure of the investigated object. Another difficulty lie...
Coastal and maritime regions and their entities face accelerated degradation due to the combined effects of environmental stressors and anthropogenic activities. Coastal degradation can be identified, visualized and estimated through periodic monitor...
Predicting the state of a dynamic system influenced by a chaotic immersion environment is an extremely difficult task, in which the direct use of statistical extrapolation computational schemes is infeasible. This paper considers a version of precede...
Over the past few years, Earth Observation (EO) has been continuously generating much spatiotemporal data that serves for societies in resource surveillance, environment protection, and disaster prediction. The proliferation of EO data poses great ch...
In this paper, the problem of estimating the current value of financial instruments using multidimensional statistical analysis is considered. The research considers various approaches to constructing regression computational schemes using quotes of...
Coaching leadership is experienced through both subjective perceptions and observable actions, but these sources do not represent equivalent constructs. This descriptive multi-case study examined coach–athlete perceptual alignment and match-obs...
Tuberculosis is a serious public health issue. It is the most prevalent cause of death from a single infectious agent and globally, it is among the top 10 causes. One of the most crucial strategies to combat the TB pandemic is to administer basic ant...
An accurate vehicle driving state observer is a necessary condition for a safe automotive electronic control system. Vehicle driving state observer is challenged by unknown measurement noise and transient disturbances caused by complex working condit...
Fiber-optic Mach–Zehnder interferometers are widely used in research areas such as telecommunications, spectroscopy, and quantum information. These optical structures are known to be affected by phase fluctuations that are usually modeled as mu...
Low-slow-small (LSS) target recognition using multi-dimensional radar remains challenging due to weak signatures, similar kinematics, and overlapping short-term Doppler patterns. Digital-array radar provides continuous, complementary Doppler-spectrum...
Background/Objectives: Sex differences in adult attention-deficit/hyperactivity disorder (ADHD) remain insufficiently characterized, particularly in clinically referred samples assessed through multidimensional and multi-informant approaches. This st...
Aging is characterized by gradual shifts in cellular and physiological processes, even in individuals who remain apparently clinically healthy. These changes reflect a coordinated decline in metabolic efficiency, immune regulation, organ function, ps...
Background/Objectives: Oral mucositis is a frequent and clinically significant acute toxicity in patients undergoing radiotherapy or chemoradiotherapy for head and neck cancer, with substantial consequences for swallowing function, nutritional status...
Earth Observation (EO) data are critical for many Geographic Information System (GIS)-based decision support systems to provide factual information. However, it is challenging for GIS to understand traditional EO data formats (e.g., Hierarchical Data...
In this study, we propose an enhanced methodology for assessing drought conditions through the systematic categorization of Condition Monitoring Observer Reports (CMORs) from Missouri between 2018 and 2024. Our approach introduces a novel classificat...
The tracking accuracy of the traditional Strong Tracking Unscented Kalman Filter algorithm (ST-UKF) decreases when the motion state of the traffic target changes significantly. A multidimensional adaptive factor-based strong tracking UKF (MAST-UKF) a...
A new fractional Brownian vector field (FBVF) is created for modeling multidimensional and multivariate fractal data. It is shown that the FBVF is a multidimensional and multivariate generalization of the classical Kolmogorov–Wiener process, al...
As a novel system, multi-dimensional space joint-observation SAR (MSJosSAR) can simultaneously acquire target information across multiple dimensions such as frequency, angle, and polarization. This capability facilitates a more comprehensive understa...
Distributed multi-dimensional classification, where multiple nodes over a network induce a multi-dimensional classifier based on their own local data and a little information exchanged from neighbors, has received extensive attention in the academic...
The so-called ‘Industrie 4.0’ provides high potential for data-driven methods in automated production systems. However, sensor and actuator data gathered during normal operation of the system is often limited to a narrow range of single, specific ope...
Research in astronomy education has traditionally focused on students’ conceptual understanding through a cognitive lens, despite growing recognition that learning is multidimensional and extends beyond the acquisition or re-organisation of ide...
Small-sided games (SSGs) are widely used in soccer training to replicate the technical, tactical, and physical demands of competition. However, their ability to reproduce the multidimensional distribution of accelerative and decelerative actions obse...
Online identification and characterization of suspended aerosols can provide a scientific basis for understanding aerosol transformations, quantitatively evaluating the impacts on air quality, public health, and the source apportionment of different...
Full 3D inversion of time-domain Airborne ElectroMagnetic (AEM) data requires specialists’ expertise and a tremendous amount of computational resources, not readily available to everyone. Consequently, quasi-2D/3D inversion methods are prevaili...
The aim of this study was to analyze the dynamics of a multidimensional object based on the Pareto curve for the Linear Matrix Inequalities (LMI) controller. The study was carried out based on an available “Blue Lady” training vessel model controller...
The current state of separation technology often neglects the multidimensional nature of real particle systems, which are distributed not only in terms of size, but also in terms of other properties, such as surface charge. Therefore, the aim of this...
In this study, an automatic Change Detection (CD) framework based on a multi-dimensional deep Siamese network was proposed for CD in bi-temporal hyperspectral imagery. The proposed method has two main steps: (1) automatic generation of training sampl...
Multidimensional line spectral estimation plays a fundamental role in communication and sensing systems, where it is often used for estimating channel parameters such as angles of arrival and time delays. Existing channel parameter estimation methods...
Multispectral sensors constitute a core earth observation imaging technology generating massive high-dimensional observations acquired across multiple time instances. The collected multi-temporal remote sensed data contain rich information for Earth...
This study examines multidimensional poverty among Khmer ethnic minority households in Vietnam’s Mekong Delta using a two-tier analytical framework. Applying the AlkireFoster methodology to primary survey data from 497 Khmer households across f...
This study examined the extent to which the dimensions of the five-factor model, Type-D personality, and multidimensional perfectionism were associated with a diurnal preference in the general population. A sample of (N = 864) individuals completed t...
Paper is in the scope of moisture-related problems which are connected with mold threat in buildings, sick building syndrome (SBS) as well as application of electronic nose for evaluation of different building envelopes and building materials. The ma...
The work represents a successful attempt to combine a gas sensors array with instrumentation (hardware), and machine learning methods as the basis for creating numerical codes (software), together constituting an electronic nose, to correct the class...
Objective: To evaluate the clinical outcome, safety and efficacy of the APrevent Vocal Implant System (VOIS) in patients with unilateral vocal fold paralysis (UVFP), with particular emphasis on the timing and impact of postoperative saline adjustment...
Drought is one of the least understood and complex natural hazards often characterized by a significant decrease in water availability for a prolonged period. It can be manifested in one or more forms as meteorological, agricultural, hydrological, an...
Objective: Talent identification in youth tennis remains challenging because current assessment approaches often evaluate physical, technical, and cognitive characteristics separately rather than within an integrated multidimensional framework. The p...
This paper develops a multi-dimensional Dynamic Time Warping (DTW) algorithm to identify varying lead-lag relationships between two different time series. Specifically, this manuscript contributes to the literature by improving upon the use towards l...
This paper uses multidimensional environmental value orientations as the segmentation bases for analyzing a natural destination tourism market of the National Forest Recreation Areas in Taiwan. Cluster analyses identify two segments, Acceptance and C...
The D-dimensional harmonic system (i.e., a particle moving under the action of a quadratic potential) is, together with the hydrogenic system, the main prototype of the physics of multidimensional quantum systems. In this work, we rigorously determin...
Forest Land Use Intensity (F-LUI) is a multidimensional and dynamic property of forest ecosystems that cannot be directly observed by Remote Sensing (RS). Existing approaches commonly quantify individual management activities, forest attributes or ec...
Up to now both information and its connection to reality do not have scientifically conclusive definitions, nor implicit origin. They emerge in observing multiple impulses’ interactive yes‒no actions modeling information bits. Each memorized bit of i...
Aiming to address the core issue that the current intelligence evaluation for Unmanned Ground Vehicles (UGVs) overly rely on static performance metrics and lack dynamic quantitative characterization of learning internalization capability (LIC), this...
The 2021 eruption of Cumbre Vieja on La Palma, Canary Islands, produced extensive lava flows and major landscape transformation, providing an opportunity to evaluate remote sensing approaches for mapping the extent of an emplaced lava flow. This stud...
Although tracking research has achieved excellent performance in mathematical angles, it is still meaningful to analyze tracking problems from multiple perspectives. This motivation not only promotes the independence of tracking research but also inc...
21 February 2023
This article reports the study protocol of a nationwide multicentric study in seven Italian regions aimed at assessing the effectiveness of a digitally supported approach for the early screening of frailty risk factors in community-dwelling older adu...
This paper presents a heading alignment procedure for drone navigation employing a single hover GNSS antenna combined with low-grade MEMs-IMU sensors. The design was motivated by the need for a drone-mounted differential interferometric SAR (DinSAR)...
The attribution of anomalous vessel behaviors is crucial for maritime traffic supervision and safety decision-making. However, existing approaches often lack the capability to systematically interpret multidimensional anomaly features and reveal thei...
A fundamental challenge in robotics is to reason with incomplete domain knowledge to explain unexpected observations and partial descriptions extracted from sensor observations. Existing explanation generation systems draw on ideas that can be mapped...
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