Molecular dynamics simulations take advantage of supercomputing environments, e.g., to solve molecular systems composed of millions of atoms. Supercomputers are increasing their computing and memory power while they are becoming more complex with the...
Keyword-based remote integrity auditing schemes effectively address the integrity of electronic medical records (EMRs) stored in the cloud. In practice, users expect to be able to perform flexible dynamic data updates while also protecting data priva...
Efficient retrieval of mathematical and structural similarities in System Dynamics models remains a significant challenge for traditional lexical systems, which often fail to capture the contextual dependencies of simulation processes. This paper pre...
Process safety helps prevent the unexpected and unplanned release of flammable and toxic chemicals, leading to poisonous gas clouds, fires, and explosions. Vapor cloud explosions (VCEs) are among the most severe hazards to humans and the environment...
In this review, the formation of the Oort Cloud is illuminated from several aspects. One is the history of the subject with an outline of the fundamental discoveries by Öpik, Oort and Hills. It is argued that the basic reason for judging Oort as...
Neighborhood selection is very important for local region feature learning in point cloud learning networks. Different neighborhood selection schemes may lead to quite different results for point cloud processing tasks. The existing point cloud learn...
This research explores how the cloud’s technological capability helps small and medium enterprises (SMEs) adapt to challenging business environments, providing long-term sustainability and strategic agility. The article uses a theoretical and q...
This paper introduces a method that can enhance the accuracy and efficiency of point cloud data registration. This method selects the centroid of the point cloud as the feature point and uses the projected distance of this feature point within the dy...
In response to the challenge of handling large-scale 3D point cloud data, downsampling is a common approach, yet it often leads to the problem of feature loss. We present a dynamic downsampling algorithm for 3D point cloud maps based on an improved v...
The substantial data volume within dynamic point clouds representing three-dimensional moving entities necessitates advancements in compression techniques. Motion estimation (ME) is crucial for reducing point cloud temporal redundancy. Standard block...
Point cloud completion reconstructs incomplete, sparse inputs into complete 3D shapes. However, in the current 3D completion task, it is difficult to effectively extract the local details of an incomplete one, resulting in poor restoration of local d...
As a kind of information-intensive 3D representation, point cloud rapidly develops in immersive applications, which has also sparked new attention in point cloud compression. The most popular dynamic methods ignore the characteristics of point clouds...
Assistive bathing robots have become a popular point due to their metrics, such as a humanoid working approach in the solution of elder care. However, the abilities of dynamic recognition and path planning are the key to obtain the advantages. This p...
The MapReduce architecture can reliably distribute massive datasets to cloud worker nodes for processing. When each worker node processes the input data, the Map program generates intermediate data that are used by the Reduce program for integration....
Cloud detection using downwelling radiation measured by infrared thermometer (IRT) has been utilized for many applications. The current study investigates the effects of disparate IRT specifications, including the dynamic range and sampling rates on...
Cloud storage services have become indispensable in resolving the constraints of local storage and ensuring data accessibility from anywhere at any time. Data deduplication technology is utilized to decrease storage space and bandwidth requirements....
Aiming at effectively generating safe and reliable motion paths for quadruped robots, a hierarchical path planning approach driven by dynamic 3D point clouds is proposed in this article. The developed path planning model is essentially constituted of...
Autonomous response networks are becoming a reality thanks to recent advances in cloud computing, Network Function Virtualization (NFV) and Software-Defined Networking (SDN) technologies. These enhanced networks fully enable autonomous real-time mana...
Three-dimensional (3D) point cloud classification methods based on deep learning have good classification performance; however, they adapt poorly to diverse datasets and their classification accuracy must be improved. Therefore, FSDCNet, a neural net...
Semantic segmentation in LiDAR point clouds has become an important research topic for autonomous driving systems. This paper proposes a dynamic graph convolution neural network for LiDAR point cloud semantic segmentation using a polar bird’s-e...
Dynamic load balancing in cloud computing is crucial for efficiently distributing workloads across available resources, ensuring optimal performance. This research introduces a novel dynamic load-balancing approach that leverages a deep learning mode...
The dynamic evolution behavior of submerged water jet cavitation clouds was studied by combining experiments and simulation. The formation, development, shedding, and collapsing process of a void cloud was analyzed by high-speed camera technology, an...
Efficient locomotion in autonomous driving and robotics requires clearer visualization and more precise map. This paper presents a high accuracy online mapping including weight matching LiDAR-IMU-GNSS odometry and an object-level highly dynamic point...
Internet of Things (IoT) is considered one of the future disruptive technologies and has attracted lots of research attention in the recent past. IoT devices are tiny sensing or actuating devices attached to daily life objects, capable of sending sen...
Nowadays, GF-1 (GF is the acronym for GaoFen which means high-resolution in Chinese) remote sensing images are widely utilized in agriculture because of their high spatio-temporal resolution and free availability. However, due to the transferrable ra...
Crop phenotyping data collection is the basis for precision agriculture and smart decision-making applications. Accurately obtaining the canopy volume of citrus trees is crucial for yield prediction, precise fertilization and cultivation management....
3D (3-Dimensional) object recognition is a hot research topic that benefits environment perception, disease diagnosis, and the mobile robot industry. Point clouds collected by range sensors are a popular data structure to represent a 3D object model....
A rapidly growing number of vehicles in recent years cause long traffic jams and difficulty in the management of traffic in cities. One of the most significant reasons for increased traffic jams on the road is random parking in unauthorized and non-p...
Cloud computing has witnessed widespread adoption across numerous sectors, primarily due to its substantial storage capacity and powerful computational resources. In this context, secure data sharing in cloud environments is critically important. Ide...
Accurate 3D semantic perception is essential for robotic operations in multi-tier caged-pigeon houses, where dense cage-mounted facilities, repetitive layouts, local geometric similarity, and dynamic objects make static-facility segmentation difficul...
Current cloud–edge collaboration collaboration architectures face challenges in security resource scheduling due to their mostly static nature, which cannot keep up with real-time attack patterns and dynamic security needs. To address this, thi...
The continuously evolving world of cloud computing presents new challenges in resource allocation as dispersed systems struggle with overloaded conditions. In this regard, we introduce OptiDJS+, a cutting-edge enhanced dynamic Johnson sequencing algo...
Driven by technologies such as the Internet of Things and artificial intelligence, smart buildings have developed rapidly, and the demand for processing massive amounts of data has risen sharply. Traditional cloud computing is confronted with challen...
Secure group communication in Vehicle Ad hoc Networks (VANETs) over open channels remains a challenging task. To enable secure group communications with conditional privacy, it is necessary to establish a secure session using Authenticated Key Agreem...
With the rapid development of cloud computing, the demand for infrastructure resources in cloud data centers has further increased, which has already led to enormous amounts of energy costs. Virtual machine (VM) consolidation as one of the important...
Attribute-Based Access Control (ABAC) has become the most suitable access control method for cloud environments due to its flexibility and fine-grained advantages. However, it suffers from issues such as insufficient dynamic adaptability and a lack o...
The irregular and highly non-uniform spatial distribution inherent to dynamic three-dimensional (3D) point clouds (DPCs) severely hampers the extraction of reliable temporal context, rendering inter-frame compression a formidable challenge. Inspired...
Point cloud segmentation constitutes a core task in 3D computer vision. However, prevailing models suffer from inherent limitations, including the absence of polarity correlation (i.e., spatial attribute-containing features derived from the separatio...
This paper proposes an algorithm for transmitting and reconstructing the estimated point cloud by temporally estimating a dynamic point cloud sequence. When a non-rigid 3D point cloud sequence (PCS) is input, the sequence is divided into groups of po...
Efficient resource allocation is a central challenge in multi-tenant cloud, fog, and edge environments, where heterogeneous tenants compete for shared resources under dynamic and uncertain workloads. Static or purely heuristic methods often fail to c...
The fire risk of cables constantly changes over time and is affected by the materials and working conditions of cables. To address its internal timing property, it is essential to use a dynamic analysis method to assess cable fire risk. Meanwhile, da...
Indoor 3D point cloud semantic segmentation is a fundamental task for fine-grained scene understanding and intelligent perception. Due to the prohibitive cost of dense point-wise annotations, weakly supervised learning has emerged as a promising alte...
Energy efficiency is a significant topic in cloud computing. Dynamic consolidation of virtual machines (VMs) with live migration is an important method to reduce energy consumption. However, frequent VM live migration may cause a downtime of service....
The reliability of petroleum offshore platform systems affects human safety and well-being; hence, it should be considered in plant design and operation in order to determine its effect on human fatality risk. Methane Vapour Cloud Explosions (VCE) in...
Reliability and safety are crucial for the operation of a dynamically tuned passive power filter (DTPPF). Safe performance of DTTPFs implies complete normal filtering without failure within a specified period. To prevent potential disaster or economi...
Rapid aerodynamic drag prediction is an important surrogate-modeling task in simulation-based vehicle design because high-fidelity computational fluid dynamics is often too expensive for screening large numbers of candidate geometries. We investigate...
Ground-based cloud image features high-spatiotemporal resolution, presenting detailed local cloud structures and valuable weather information, which are crucial for meteorological forecasting. However, the inherent fuzziness and dynamism of ground-ba...
We present new results of our studies of zonal and meridional winds in both hemispheres of Venus, using ground- and space-based coordinated observations. The results obtained from telescope observations were retrieved with a Doppler velocimetry metho...
It is expected that the pervasive deployment of multi-tier 5G-supported Mobile-Fog-Cloudtechnological computing platforms will constitute an effective means to support the real-time execution of future Internet applications by resource- and energy-li...
Security assessment of ironmaking plants is one of the crucial means to promote their sustainable development. However, the disparate nature of subsystems within these plants, along with network inconsistencies and isolated data, obstruct a thorough...
of 62