This paper introduces an efficient and accurate interpolator for NURBS (non-uniform rational B-spline) curves, addressing the challenge of regulating feedrate under machining accuracy and dynamic constraints, particularly at sensitive corners. A recu...
The game of life (GL), a type of two-dimensional cellular automaton, has been the subject of many studies because of its simple mechanism and complex behavior. In particular, the construction of logic circuits using the GL has helped to extend the co...
Accurate attitude estimation for highly dynamic spacecraft relies on robust fusion of star-tracker and inertial measurements. However, asynchronous sensing, motion blur in star images, and delayed star-tracker outputs can significantly degrade estima...
With the increasing complexity of applications, many delay-sensitive and compute-intensive services have posed significant challenges to mobile devices. Addressing how to efficiently allocate heterogeneous network resources to meet the computing and...
Airborne Light Detection and Ranging (LiDAR) is widely used in digital elevation model (DEM) generation. However, the very large volume of LiDAR datasets brings a great challenge for the traditional serial algorithm. Using parallel computing to accel...
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...
Cyber-physical energy systems provide a networked solution for safety, reliability and efficiency problems in smart grids. On the demand side, the secure and trustworthy energy supply requires real-time supervising and online power quality assessing....
Positioning asynchronous architectures based on time measurements are reaching growing importance in Local Positioning Systems (LPS). These architectures have special relevance in precision applications and indoor/outdoor navigation of automatic vehi...
This paper introduces RWA-BFT, a reputation-weighted asynchronous Byzantine Fault Tolerance (BFT) consensus algorithm designed to address the scalability and performance challenges of blockchain systems in large-scale IoT scenarios. Traditional centr...
In high-throughput network perimeters, traditional single packet authorization (SPA) for zero trust network access faces performance bottlenecks and memory-safety risks from user-space packet capture and untrusted rich execution environments. To addr...
Novel image sensors transduce the stream of photons directly into asynchronous electrical pulses, rather than forming an image. Classical approaches to vision start from a good quality image and therefore it is tempting to consider image reconstructi...
A Spiking Neural Network (SNN) is realized within a 65 nm CMOS process to demonstrate the feasibility of its constituent cells. Analog hardware neural networks have shown improved energy efficiency in edge computing for real-time-inference applicatio...
Federated learning (FL) offers a promising solution in edge computing to overcome bandwidth limitations and privacy concerns associated with traditional cloud-based training. However, current FL methods often suffer from transmission delay and excess...
Traditional frame-based cameras, despite their effectiveness and usage in computer vision, exhibit limitations such as high latency, low dynamic range, high power consumption, and motion blur. For two decades, researchers have explored neuromorphic c...
The Internet of Things (IoT) opens up tremendous opportunities to provide location-based applications. However, despite the services around a user being physically adjacent, common IoT platforms use a centralized structure, like a cloud-computing arc...
The design and creation of groupware tools is a complex task that usually requires the participation of different stakeholders (software engineers, designers, etc.), either working at the same time or collaborating asynchronously. This paper describe...
The space information networks (SIN) have a series of characteristics, such as strong heterogeneity, multiple types of resources, and difficulty in management. Aiming at the problem of resource allocation in SIN, this paper firstly establishes a hier...
The method of Semantic Background Subtraction (SBS), which combines semantic segmentation and background subtraction, has recently emerged for the task of segmenting moving objects in video sequences. While SBS has been shown to improve background su...
With the immersion of a plethora of technological tools in the early post-COVID-19 era in university education, instructors around the world have been at the forefront of implementing hybrid learning spaces for knowledge delivery. The purpose of this...
Super points detection plays an important role in network research and application. With the increase of network scale, distributed super points detection has become a hot research topic. The key point of super points detection in a multi-node distri...
The deployment of Federated Learning (FL) in edge environments is often impeded by system heterogeneity, non-independent and identically distributed (non-IID) data, and constrained communication resources, which collectively hinder training efficienc...
Assessing e-learning students’ satisfaction with lecturers’ interactions in asynchronous forums is essential for enhancing teaching and learning processes. The discussion forum allows students to share comments and ideas with peers or lec...
This paper proposes an interference detection method for multiuser-multiple input multiple output (MU-MIMO) transmission, which utilizes periodical preamble signals in the frequency domain and the concept of full-duplex transmission when assuming idl...
The event camera, a new bio-inspired vision sensor with low latency and high temporal resolution, has brought great potential and demonstrated a promising application in machine vision and artificial intelligence. Corner detection is a key step of ob...
The High Intensity Muon Beams (HIMB) project at the Paul Scherrer Institute (PSI) will deliver muon beams with unprecedented intensities of up to
This review examines the technologies shaping real-time web application development, with particular attention to bidirectional communication protocols, distributed reactive architectures, and computing platforms designed for low-latency, high-concur...
Accurate and real-time localization for unmanned vehicles in complex motion environments is challenged by asynchronous multi-sensor measurements, time-varying measurement quality, and the growing computational burden of long-term factor graph optimiz...
Vision transformers (ViTs) demonstrate exceptional performance in numerous computer vision tasks owing to their self-attention modules. Despite improved network performance, transformers frequently require significant computational resources. The inc...
A review of the basic Hansen’s ideal frame algorithms for accurate numerical integration of perturbed elliptic motion is carried out. The fundamental approaches rely on the use of nonsingular variables and differ in the ways in which the ellips...
Spectral models, due to their stability and efficiency, have become one of the most popular approaches for implementing numerical weather prediction systems. Given the complexity of these models, they often require the use of multi-node computing res...
Neuromorphic computing, a brain-inspired non-Von Neumann computing system, addresses the challenges posed by the Moore’s law memory wall phenomenon. It has the capability to enhance performance while maintaining power efficiency. Neuromorphic c...
Measuring the similarity between a pair of trajectories is the basis of many spatiotemporal clustering methods and has wide applications in trajectory pattern mining. However, most measures of trajectory similarity in the literature are based on prec...
Stroke continues to impose an enormous morbidity and mortality burden worldwide. Stroke survivors often incur debilitating consequences that impair motor function, independence in activities of daily living and quality of life. Rehabilitation is a pi...
An efficient parallel computation using graphics processing units (GPUs) is developed for studying the electromagnetic (EM) backscattering characteristics from a large three-dimensional sea surface. A slope-deterministic composite scattering model (S...
This paper describes an interactive control algorithm, called Triangle Formation Algorithm (TFA), used for three neighboring robotic sensors which are distributed randomly to self-organize into and equilateral triangle (E) formation. The algorithm is...
The correlation-based synthetic aperture radar imaging technique, termed radar coincidence imaging, is extended to a fully multistatic multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) configuration. Within this framework, we explo...
Mobile edge computing (MEC) systems empowered by energy harvesting (EH) significantly enhance sustainable computing capabilities for mobile devices (MDs). This paper investigates a multi-user multi-server MEC network, in which energy-constrained user...
Due to its links to computer science (CS), teaching computational thinking (CT) often involves the handling of algorithms in activities, such as their implementation or analysis. Although there already exists a wide variety of different tasks for var...
Single-photon avalanche detectors (SPADs) have significant applications in fields such as autonomous driving. However, processing massive amounts of background data requires substantial storage and computational resources. This paper designs a linear...
Federated Learning (FL) revolutionizes collaborative machine learning among Internet of Things (IoT) devices by enabling them to train models collectively while preserving data privacy. FL algorithms fall into two primary categories: synchronous and...
Cortical neurons receive mixed information from the collective spiking activities of primary sensory neurons in response to a sensory stimulus. A recent study demonstrated an abrupt increase or decrease in stimulus intensity and the stimulus intensit...
This study addresses computational challenges in the immersed boundary method (IBM) with the pressure implicit with split operator (PISO) algorithm for simulating incompressible flows. We introduce a novel time-step splitting method to implement comm...
The rapid development of Unmanned Aerial Vehicle (UAV) swarm technology has led to its increasingly vital role in intelligent transportation, environmental monitoring, and emergency response. However, existing centralized identity authentication mech...
Over the past decade, wireless sensor network research primarily relied on highly-integrated commercial off-the-shelf radio chips. The rigid silicon implementation of the radio stack restricted access to the lower layers; thus, research focused mainl...
Facial landmark localization is a significant yet challenging computer vision task, whose accuracy has been remarkably improved due to the successful application of deep Convolutional Neural Networks (CNNs). However, CNNs require huge storage and com...
The exact nature of thermal processes occurring in an electric motor is often unknown. Thus, the estimation of temperature rise using mathematical models and computational experiments is becoming increasingly important. Thermal analysis is the key de...
This paper focuses on dealing with the problem of co-designing a fuzzy-basis-dependent event generator and an asynchronous filter of fuzzy Markovian jump systems via event-triggered non-parallel distribution compensation (non-PDC) scheme. The introdu...
As restricted resources have seriously limited the computational performance of massive Internet of things (IoT) devices, better processing capability is urgently required. As an innovative technology, multi-access edge computing can provide cloudlet...
Recurrent neural networks are studied along two largely parallel tracks: as machine-learning models evaluated by task performance and as computational-neuroscience models of cortical circuits evaluated by dynamical realism. Reservoir computing offers...
Early warning consists of monitoring precursors of a potential hazard to understand if it is evolving to a real risk and then be able to orchestrate an early response before the event happens in order to reduce its impact and damages. It mainly consi...
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