Unmanned Aerial Systems, hereafter referred to as UAS, are of great use in hazard events such wildfire due their ability provide high-resolution video imagery over areas deemed too dangerous for manned aircraft and ground crews. This aerial perspective allows identification ground-based hazards spot fires fire lines, communicate this information with fighting Current technology relies on visual interpretation UAS imagery, little no computer-assisted automatic detection. With the help big...

Connected and automated vehicles (CAVs) provide various valuable advanced services to manufacturers, owners, mobility service providers, transportation authorities. As a result, large number of CAV applications have been proposed improve the safety, mobility, sustainability system. With increasing connectivity automation, cybersecurity connected system (CATS) has raised attention community in recent years. Vulnerabilities CAVs can lead breakdowns compromise safety (e.g., causing crashes),...

With the rapid development and gradual perfection of GNSS in recent years, improving real-time service performance has become a research hotspot. In single-point positioning, broadcast ephemeris is used to provide space–time reference. However, orbit parameters have meter-level errors, no mathematical model can simulate variation this, which restricts positioning accuracy GNSS. Based on this background, paper uses BP (Back Propagation) neural network PSO (Particle Swarm Optimization)–BP...

To reduce power consumption of smartphones, this work proposes a novel discontinuous reception (DRX)-based saving mechanism for LTE-A networks supporting multi-services. The designs the proposed mainly include highest priority-controlled DRX (HPC-DRX) and traffic regulation plus time slicing (TRTS) schemes. In our HPC-DRX/TRTS, lower priority never wakes user equipments (UEs) up all incoming UEs is temporarily buffered at evolved Node B (eNB) then transmitted in bursts using overall...

Recent advancements in deploying deep neural networks (DNNs) on resource-constrained devices have generated interest input-adaptive dynamic (DyNNs). DyNNs offer more efficient inferences and enable the deployment of DNNs with limited resources, such as mobile devices. However, we discovered a new vulnerability that could potentially compromise their efficiency. Specifically, investigate whether adversaries can manipulate DyNNs' computational costs to create false sense To address this...

Conventional learning methods simplify the bilinear model by regarding two intrinsically coupled factors independently, which degrades optimization procedure. One reason lies in insufficient training due to asynchronous gradient descent, results vanishing gradients for variables. In this paper, we introduce a Cogradient Descent algorithm (CoGD) address problem, based on theoretical framework coordinate of hidden variables via projection function. We solve one variable considering its...

This paper presents an analysis of vehicle breakdown duration on motorways. The distribution was shown to be statistically significantly different for three categories type and were conform a Weibull distribution. A predictive model developed, based fuzzy logic. variables used in this were: type, time, location reporting mechanism. performance the tested with encouraging results. Clustering data due rounding errors when operator reported incident 60 120 minutes. unexplained variation...

Perceived effectiveness (PE) is a validated tool for predicting the potential impact of anti-tobacco public service announcements (PSAs). We set out to evaluate added predictive value facial expression analysis when combined with PE in remote (online) survey. Each 302 tobacco users watched 3 PSAs and allowed transmission webcam videos from which metrics “attention” (head position) “facial action units” (FAU) were computed. The participants completed scales their subjective emotions,...

In this work, we tackle the task of learning generalizable 3D human Gaussians from a single image. The main challenge for is to recover detailed geometry and appearance, especially unobserved regions. To end, propose single-view Human Gaussian model (HGM), diffusion-guided framework modeling We design diffusion-based coarse-to-fine pipeline, where diffusion adapted refine novel-view images rendered coarse model. refined are then used together with input image learn Although effective in...

Cooperative perception that integrates sensing capabilities from both infrastructure and vehicle sensors can greatly benefit the transportation system with respect to safety data acquisition. In this study, we conduct a preliminary evaluation of such by integrating portable lidar-based detection (namely, Traffic Scanner [TScan]) Society Automotive Engineers (SAE) Level 4 connected automated (CAV). Vehicle-to-everything (V2X) communication devices are installed on TScan CAV enable real-time...

The roadside units (RSUs) based on traditional grid has high carbon footprint and deployment cost in vehicle dedicated network. An ideal green alternative become an important issue Vehicular Ad-Hoc Networks (VANETs). In this paper, we propose a novel framework of energy harvesting cooperation to maximize the life cycle VENETs. VANET scenario, RSU node can harvest from nature also receive down steam dispatch maintain needed for data transmission, may transfers portion obtained energies by...

The autonomous vehicle navigation system and the intelligent traffic need real-time routing planning in engineering management. Urban road intersections play bottlenecks of urban roads, contributing a great deal to loss travel time due interference, management control. detection intersection is important for obtaining regulation information. This paper proposes method detect based on floating car data that typically timestamped geo-localization, direction speed directly collected by moving...

Recent research on vehicular cybersecurity has highlighted the known vulnerabilities and exploits that plague in-vehicular networks; in particular, communication protocol governing network, Control Area Network (CAN), been a frequent often fruitful target of related attacks. Accordingly, focus this project is to investigate application encryption algorithms network evaluate performance characteristics said when used context. This current paper includes examination a) maximum acceptable...