The evolution of the internet towards supporting time-critical applications, such as industrial cyber-physical systems (CPSs) and autonomous systems, has created an urgent demand for networks capable of providing deterministic, low-latency communicat...
Time-Sensitive Networking (TSN) is a set of Ethernet standards aimed to improve determinism in packet delivery for converged networks. The main goal is to provide mechanisms that enable low and predictable transmission latency and high availability f...
Manual calibration of nuclear medicine scanners currently relies on handling phantoms containing radioactive sources, exposing personnel to high radiation doses and elevating cancer risk. We designed an automated detection framework for robotic inspe...
Sparse rewards remain a major obstacle to efficient reinforcement learning (RL), particularly in long-horizon goal-reaching tasks where little feedback is available before successful termination. This difficulty is further complicated by time-limited...
The traffic scheduling mechanism in Time-Sensitive Networking (TSN) is the key to guaranteeing the deterministic transmission of traffic. However, when time-sensitive traffic and non-time-sensitive traffic are transmitted together, traffic scheduling...
Time series clustering plays a vital role in various analytical and pattern recognition tasks by partitioning structurally similar sequences into semantically coherent groups, thereby facilitating downstream analysis. However, building high-quality c...
To support more advanced functionality in vehicles, there is the challenge of deterministic and reliable transmission of sensor data and control signals. Time-sensitive networking (TSN) is the most promising candidate to meet this demand by leveragin...
Accurate trajectory tracking is a key requirement in unmanned ground vehicles (UGVs) operating in autonomous driving, mobile robotics, and industrial automation. In wireless Time-Sensitive Networking (WTSN) scenarios, trajectory accuracy strongly dep...
Time-Sensitive Networking (TSN) has emerged as a critical communication protocol for automotive Ethernet to support the high-bandwidth, real-time, and deterministic transmission requirements of next-generation in-vehicle networks. However, a clear an...
Temporal monitoring of bioprocesses is inherently complex because process variables do not evolve independently over time, and their interpretation changes as the reaction progresses. In many existing abnormality detection methods, sensor signals are...
This review analyzes how recent electric-vehicle LCAs have been carried out, emphasizing goals and scope, functional units, system boundaries (cradle-to-grave and well-to-wheel), and attributional versus consequential modeling rather than reporting o...
Wildlife strikes are a persistent aviation safety concern because bird strike risk is shaped by dynamic interactions among weather, bird movement, airport operations, seasonality, and time of day. Although traditional machine learning methods have be...
As the next frontier in wireless communication, the landscape of 6G technologies is characterized by its rapid evolution and increasing complexity, driven by the need to address global challenges such as ubiquitous connectivity, ultra-high data rates...
To address the challenges posed by AI technologies, an increasing number of organizations encourage or require employees to integrate AI into their work processes. Despite the extensive research that has explored AI applications in the workplace, lim...
In future 6G networks, real-time and accurate vehicular data are key requirements for enhancing the data-driven multi-access edge computing (MEC) applications. Existing estimation techniques to forecast vehicle position aim to meet the real-time data...
Coordinating whole-body shape generation, geometric object caging, and collision-aware transportation remains challenging for hyper-redundant robots. This study presents a framework integrating Transformer-based backbone prediction, cage-preserving g...
The relationship between environmental awareness and actionable change is complex. While extensive literature examines the links between green ideology and eco-friendly behavior, few studies focus on how green ideology influences transportation choic...
Recent studies have shown a growing prevalence of autism spectrum disorders, accompanied by heightened concerns about the impact of misinformation on autism stigmatization, shaping public perceptions of autism. With the increase in autism cases world...
Given the significant impact of Generative AI (GenAI) in the workplace, there are surprisingly few empirical studies examining how employees’ GenAI awareness shapes differently oriented job crafting behaviors. In organizations, understanding th...
Background: Despite the prevalence and incidence of kidney stones progressively increasing worldwide, public awareness of this condition remains unclear. Understanding trends of awareness can assist healthcare professionals and policymakers in planni...
This paper presents a sensor-orientated approach to on-orbit position uncertainty generation and quantification for both ground-based and space-based surveillance applications. A mathematical framework based on the least squares formulation is develo...
The context ultimately decides on mobility options and thus shapes mobility behavior. Nudges are an increasingly used strategy for promoting sustainable modes of everyday mobility. However, in most cases, the design of nudges and the triggers for iss...
Time-sensitive networking (TSN) is a kind of network communication technology applied in fields such as industrial internet and intelligent transportation, capable of meeting the application requirements for precise time synchronization and low-laten...
The efficiency of energy usage applied to robots that implement autonomous duties such as floor cleaning depends crucially on the adopted path planning strategies. Energy-aware for complete coverage path planning (CCPP) in the reconfigurable robots r...
Precise, non-destructive detection of fruit maturity is a cornerstone of modern precision agriculture, directly impacting harvest scheduling and post-harvest quality control. In the case of strawberries (Fragaria × ananassa), in-field automated...
Shape-sensing optical fibers have become increasingly important in applications requiring flexible navigation, spatial awareness, and deformation monitoring. Fiber Bragg Grating (FBG) sensors inscribed in multi-core optical fibers have been democrati...
Accurate and efficient detection of industrial glass defects poses persistent practical challenges. Small, low-contrast defects are difficult to distinguish, while background redundancy in high-resolution line-scan images increases computational cost...
This paper explores the intricate relationship between our personal experiences of space and the autobiographical nature of our geography. Our geographical awareness is profoundly shaped by the places we have been, encompassing a rich tapestry of pla...
To obtain the complete shape and pose of corn under occlusion, this study proposes a point cloud completion algorithm for completing the fragmented corn point cloud after segmentation. Considering that this work focuses on a single-class crop—c...
Visual Patient technology is a situation awareness-oriented visualization technology that translates numerical and waveform patient monitoring data into a new user-centered visual language. Vital sign values are converted into colors, shapes, and rhy...
Both feeling and thought operate largely through a process of associations. Some of these are learned; some seem to be transcultural. In Western art it has long been assumed that certain arrangement of sounds, shapes, and colors evoke particular emot...
Social media platforms have become central sites of identity construction, where visibility and legitimacy are shaped through algorithmic systems, aesthetic conventions, and platform economies. This paper approaches online personas through the lens o...
Currently, Poland has been facing a process of intensive changes in the energy sector, motivated by the strengthening of the goals of the climate and energy policy at the European level. A key challenge for energy transition in Poland is to build an...
This study investigates how climate change literacy (CCL) and institutional contexts shape the climate-related behaviors of Taiwan’s public officials. Drawing on a 2024 national survey of 1940 civil servants, we apply hierarchical and comparati...
NFT prices are shaped by heterogeneous signals including visual appearance, textual narratives, transaction trajectories, and on-chain interactions, yet existing studies often model these factors in isolation and rarely unify multimodal alignment, te...
Early-exit deep neural networks (DNNs) can reduce edge-inference latency, but abrupt variations in wireless and computing resources can destabilize split-inference policies. This paper proposes a meta-learning-driven adaptive control framework for jo...
Singing pedagogy has increasingly adopted guide awareness through the use of meaningful real-time visual feedback. Technology typically used to study the voice can also be applied in a singing lesson, aiming at facilitating students’ awareness...
The aim of this systematic review is to analyze the attitudes and practices adopted by citizens in waste reduction, separation, and recycling, taking into consideration specific socio-demographic factors such as gender, age, income level, and level o...
Residential photovoltaic (PV)–battery systems are increasingly deployed to reduce electricity costs under time-of-use and demand-charge tariffs, yet their economic value depends critically on how storage is operated over time. Effective control...
Wideband signal detection and recognition (WSDR) is considered an effective technical means for monitoring and analyzing spectra. The mainstream technical route involves constructing time–frequency representations for wideband sampled signals a...
Using a Poisson regression model with a quadratic term and data from a 2022 survey of rice farmers across 10 counties in China’s Jianghan Plain, this study examines how the off-farm income shares are associated with the interplay between surviv...
A novel facial landmark localization method, termed TSDM, is proposed by integrating T-shaped features with the Supervised Descent Method (SDM). Facial landmark localization is critical for driver fatigue and attention detection in intelligent cockpi...
In a world that grows increasingly aware of ecological problems such as global warming, rising sea levels, and pollution, we need to reconsider how we connect ourselves to the natural world around us. In this paper, we view makerspaces as ideal locat...
Background: The main objective of this study was to carry out an online questionnaire in order to assess dentists’ knowledge and perception of dental materials submitted to high temperatures, helping to clarify and raise awareness of possible g...
This study examines Malaysian consumers’ perceptions toward purchasing electric vehicles (EVs) in the context of increasing global efforts to promote sustainable mobility and reduce carbon emissions. Despite government initiatives and incentive...
This study addresses the insufficient representation of moving ground targets in conventional UAV air–ground risk assessment, which typically relies on static population distributions or instantaneous target locations and therefore fails to cap...
Converging millimetre-wave (mmWave) radio access with passive optical network (PON) fronthaul under the Open RAN (O-RAN) architecture promises unprecedented capacity for beyond-5G and 6G systems. Yet today, dynamic bandwidth allocation (DBA) in the P...
Vehicle pose estimation with LIDAR plays a crucial role in autonomous driving systems. It serves as the fundamental basis for functions such as tracking, path planning, and decision-making. However, the majority of current vehicle pose estimation tec...
In spite of significant research efforts, the existing scene text detection methods fall short of the challenges and requirements posed in real-life applications. In natural scenes, text segments exhibit a wide range of shape complexities, scale, and...
To address the challenging requirements of citrus detection in complex orchard environments, this paper proposes ACDNet (Adaptive Citrus Detection Network), a novel deep learning framework specifically designed for automated citrus harvesting. The pr...
of 7