Background: The integration of markerless motion capture systems such as OpenCap with force platforms expands the possibilities of biomechanical analysis in low-cost environments; however, it requires robust temporal synchronization procedures in the...
Predictive monitoring of injection operations requires evidence that warning rules transfer across fault conditions and loading rates. We develop a seven-variable representation of mechanical, hydraulic, and acoustic measurements and retrospectively...
Overlapping forecasting windows can conceal the limited independence of event archives. We evaluated seven models using 2039 records from 41 events at Hongjiata Hydrological Station during 2016–2025. Telemetry elevations were harmonized by addi...
Simulation and simulation-based optimisation support humanitarian logistics and disaster-management decisions under uncertainty, but the evidential basis of their recommendations depends on how clearly publications connect model specification, comput...
Accurate evaluation of the shank-to-vertical angle (SVA) is important for optimizing lower-limb alignment during gait, particularly during ankle–foot orthosis (AFO) tuning. This study investigated the validity of a wearable posture sensor for c...
Robust object detection in autonomous driving is challenged by inherent limitations of conventional frame-based cameras, such as motion blur and limited dynamic range. In contrast, event-based cameras, which operate asynchronously and capture rapid c...
Credential-based authorization offers interesting advantages for ubiquitous scenarios involving limited devices such as sensors and personal mobile equipment: the verification can be done locally; it offers a more reduced computational cost than its...
Dynamic Vision Sensor (DVS) is an event-based imaging technology inspired by biological photoreceptors, which holds great promise for edge computing. The event streams produced by DVS are often contaminated by Background Activity (BA) noise and hot-p...
Video deblurring aims at removing the motion blur caused by the movement of objects or camera shake. Traditional video deblurring methods have mainly focused on frame-based deblurring, which takes only blurry frames as the input to produce sharp fram...
Event-based cameras, as a revolutionary class of dynamic vision sensors, offer transformative advantages for capturing transient mechanical phenomena through their asynchronous, per-pixel brightness change detection mechanism. These neuromorphic sens...
Flashover events can induce rapid surface condition changes on outdoor ceramic insulators, while early-stage degradation is typically assessed indirectly through long-term ageing or electrical diagnostics. This study proposes an event-based, surface-...
To address the issues of insufficient robustness, large depth recovery errors, and poor scene adaptability currently present in the initialisation phase of event-based stereo visual inertial SLAM systems, we propose a global BA initialisation method...
In this paper, a novel approach to detect incipient slip based on the contact area between a transparent silicone medium and different objects using a neuromorphic event-based vision sensor (DAVIS) is proposed. Event-based algorithms are developed to...
Unmanned aircraft vehicles (UAVs) are now used to support security precautions in search and rescue operations to track and evaluate critical services, to provide cybersecurity measures by transporting security supply chain management (SCM) to sports...
Permeable pavement (PP) is used worldwide to mitigate surface runoff in urban areas. Various studies have examined the factors governing the hydrologic performance of PP. However, relatively little is known about the relative importance of these gove...
A soil erosion and sediment transport model (WRF-Hydro-Sed) is introduced to WRF-Hydro. As a process-based, fully distributed soil erosion model, WRF-Hydro-Sed accounts for both overland and channel processes. Model performance is evaluated using obs...
This paper presents a digitally controlled current-mode synaptic weighting cell in 28 nm FD-SOI CMOS for low-complexity Multi-Layer Perceptron (MLP) inference in event-based Non-Intrusive Load Monitoring (NILM). A compact bias-free [16,16] MLP is tra...
Analyzing naturalistic driving behavior recorded with in-car cameras is an ecologically valid method for measuring driving errors, but it is time intensive and not easily applied on a large scale. This study validated a semi-automated, computerized m...
This study proposes a methodology that combines the advantages of the event-based and continuous models, for the derivation of the maximum flow and maximum hydrograph volume frequency curves, by combining a stochastic continuous weather generator (th...
Robotic systems are increasingly being deployed in mining operations to support tasks such as inspection, navigation, environmental monitoring, and safety supervision. However, mining environments present significant challenges for robotic perception...
Detecting internal defects in narrow and curved pipelines remains a significant challenge, due to the difficulty of achieving reliable defect perception under low-light conditions and generating collision-free motion trajectories. To address these ch...
Eye movement classification, particularly the identification of fixations and saccades, plays a vital role in advancing our understanding of neurological functions and cognitive processing. Conventional modalities of data, such as RGB webcams, often...
An event camera generates an event stream based on changes in brightness, retaining only the characteristics of moving objects, and addresses the high power consumption associated with using high-frame-rate cameras for high-speed eye-tracking tasks....
Chronic obstructive pulmonary disease (COPD) is a significantly concerning disease, and is ranked highest in terms of 30-day hospital readmission. Generally, physical activity (PA) of daily living reflects the health status and is proposed as a stron...
This paper presents an overview and formalization of the Functional Mock-up Interface (FMI) 3.0. The formalization captures the new FMI 3.0 standard and is intended to be used as an introduction for conceptualizing the use of clocks in the FMI standa...
Machine learning (ML) models utilizing high-frequency Internet of Things (IoT) monitoring data offer significant potential for stream-level nowcasting. The assessment of model performance is often a challenging task because conventional approaches ar...
The quasi-synchronization for a class of general heterogeneous neural networks is explored by event-based impulsive control strategy. Compared with the traditional average impulsive interval (AII) method, instead, an event-triggered mechanism (ETM) i...
Since smart cities aim at becoming self-monitoring and self-response systems, their deployment relies on close resource monitoring through large-scale urban sensing. The subsequent gathering of massive amounts of data makes essential the development...
Arrival-time picking is a critical step in microseismic data processing, and thus the quality control of arrival results is necessary. Conventional picking methods may be inaccurate or inconsistent due to varied signal-to-noise ratios (SNR) and wavef...
Traditional drug discovery is a high-risk, time-consuming, and costly endeavor. Drug repurposing has emerged as a pivotal strategy to overcome these challenges by identifying new therapeutic indications for approved drugs, thereby significantly reduc...
Digital Elevation Model (DEM) resolution plays a critical role in hydraulic flood modelling by influencing inundation accuracy, spatial precision and computational efficiency. However, limited studies have simultaneously evaluated both inundation acc...
Various development and validation methods for cyber-physical systems such as Controller-Hardware-in-the-Loop (C-HIL) testing strongly benefit from a seamless integration of (hardware) prototypes and simulation models. It has been often demonstrated...
Due to the socioeconomical impact of water extremes in plain areas, there is a considerable demand for suitable strategies aiding in the management of water resources and rainfed crops. Numerical models allow for the modelling of water extremes and t...
In weather radar applications, the Z-R relationship is considered one of the most crucial factors for providing quality quantitative precipitation estimates. However, the relationship’s parameters vary in time and space, making the derivation o...
Wireless smart sensors (WSS) have been proposed as an effective means to reduce the high cost of wired structural health monitoring systems. However, many damage scenarios for civil infrastructure involve sudden events, such as strong earthquakes, wh...
The diverse rating scales used by brokerage firms pose significant challenges for aggregating analyst recommendations in financial research. We develop a momentum-based normalization framework that transforms heterogeneous rating changes into standar...
Precipitation is one of the essential variables in rainfall-runoff modeling. For hydrological purposes, the most commonly used data sources of precipitation are rain gauges and weather radars. Recently, multi-satellite precipitation estimates have ga...
Energy disaggregation algorithms disintegrate aggregate demand into appliance-level demands. Among various energy disaggregation approaches, non-intrusive load monitoring (NILM) algorithms requiring a single sensor have gained much attention in recen...
Event cameras provide high temporal resolution and sparse asynchronous output for small-target monitoring. However, distant weak targets often generate sparse and fragmented events that are easily obscured by responses from background structures and...
Streams in the Kenai River watershed are characterized by a fish-rich environment. The commercial fishing industry and recreational users compete for the fish in these streams, and resource managers strive to balance both groups’ needs while ma...
Integrating a partnership with potentially stronger suppliers is widely acknowledged as a contributor to the organizational competitiveness of a supply chain. This paper proposes an event-based model which lists the events related with all phases of...
The goal of the present study is to integrate different datasets in cell biology to derive additional quantitative information about a gene or protein of interest within a single cell using computational simulations. We propose a novel prototype cell...
Runoff prediction in limited-data areas is vital for hydrological applications, such as the design of infrastructure and flood defenses, runoff forecasting, and water management. Rainfall–runoff models may be useful for simulation of runoff generatio...
Nowadays, energy management aims to propose different strategies to utilize available energy resources, resulting in sustainability of energy systems and development of smart sustainable cities. As an effective approach toward energy management, non-...
(1) Background: Rider–horse coordination underpins equestrian performance; yet, its definition, quantitative indicators, and measurement methods remain inconsistent across Olympic disciplines. This scoping review mapped the constructs, metrics,...
Sound event detection (SED) is of great practical and research significance owing to its wide range of applications. However, due to the heavy reliance on dataset size for task performance, there is often a severe lack of data in real-world scenarios...
We compare three hydrological models of different complexities, GR4H (lumped, continuous), SMASH (distributed, continuous), and MARINE (distributed, event-based), for Mediterranean flash flood modeling. The objective was to understand how differently...
Unmanned aerial vehicle (UAV) navigation in indoor environments is challenging due to varying light conditions, the dynamic clutter typical of indoor spaces, and the absence of GNSS signals. In response to these complexities, emerging sensors, such a...
This paper is part of a study of intelligent architectures for distributed control and communications systems. The study focuses on optimizing control systems by evaluating the performance of middleware through quality of service (QoS) parameters and...
Flooding remains one of the most disruptive and costly natural hazards worldwide. Conventional approaches for estimating flood damage cost rely on empirical loss curves or historical insurance data, which often lack spatial resolution and predictive...
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