Efficient resource allocation and task scheduling remain fundamental challenges in cloud computing because of resource heterogeneity, dynamic workload characteristics, and the increasing demand for scalable, energy-efficient, and sustainable cloud in...
Cloud computing has transformed the delivery of modern applications and services by providing scalable, flexible, and cost-effective access to computing resources. One of the most critical challenges in cloud environments is the efficient distributio...
Distributed Kubernetes clusters provide robust solutions for geo-redundancy and fault tolerance in modern cloud architectures. However, default scheduling mechanisms primarily optimize for resource availability, often neglecting network topology, int...
Kubernetes clusters are deployed across data centers for geo-redundancy and low-latency access, resulting in new challenges in scheduling workloads optimally. This paper presents a practical evaluation of network-aware scheduling in a distributed Kub...
Light Detection and Ranging (LiDAR), which applies light in the formation of a pulsed laser to estimate the distance between the LiDAR sensor and objects, is an effective remote sensing technology. Many applications use LiDAR including autonomous veh...
Achieving long-term stable optimization in complex industrial processes (CIPs) is notoriously challenging due to their unclear physical/chemical reaction mechanisms, fluctuating operating conditions, and stringent regulatory constraints. A significan...
Mobile communication technology is evolving from 4G to 5G. Compared to previous generations, 5G has the capability to implement latency-critical services, such as autonomous driving, real-time AI on handheld devices and remote drone control. Multi-ac...
In the fields of meteorological simulation and computer graphics, precise simulation of clouds has been a recent research hotspot. The existing cloud modeling methods often ignore the differentiated characteristics of cloud layers at different height...
Cloud recognition is a basic task in ground meteorological observation. It is of great significance to accurately identify cloud types from long-time-series satellite cloud images for improving the reliability and accuracy of weather forecasting. How...
This paper proposes a single-stage adaptive multi-scale noise filtering algorithm for point clouds, based on feature information, which aims to mitigate the fact that the current laser point cloud noise filtering algorithm has difficulty quickly comp...
As one of the world’s most crucial food crops, maize plays a pivotal role in ensuring food security and driving economic growth. The diversification of maize variety breeding is significantly enhancing the cumulative benefits in these areas. Pr...
High-resolution optical remote sensing imagery plays a crucial role in monitoring the Earth’s surface. However, cloud obstruction and spectral confusion between clouds and snow significantly compromise data quality and application reliability,...
Monitoring harmful algal blooms (HABs) in freshwater over regional scales has been implemented through mapping chlorophyll-a (Chl-a) concentrations using multi-sensor satellite remote sensing data. Cloud-free satellite measurements and a sufficient n...
We propose NPMV-SLAM, an RGB-Depth neural implicit dense SLAM system based on multi-resolution voxels and feature point clouds. The method demonstrates exceptional performance in tracking accuracy and reconstruction quality, aiming to address the sho...
Accurate urban
Remote sensing images are usually contaminated by cloud and corresponding shadow regions, making cloud and shadow detection one of the essential prerequisites for processing and translation of remote sensing images. Edge-precise cloud and shadow segm...
Modern robotic exploratory strategies assume multi-agent cooperation that raises a need for an effective exchange of acquired scans of the environment with the absence of a reliable global positioning system. In such situations, agents compare the sc...
Plant phenotyping is crucial for advancing precision agriculture and modern breeding, with 3D point cloud segmentation of plant organs being essential for phenotypic parameter extraction. Nevertheless, although existing approaches maintain segmentati...
The leg structure of swine is closely related to their robustness and longevity. Animals with sound legs generally have longer productive lifespans and higher reproductive efficiency, whereas leg defects can markedly impair performance and shorten se...
One of the most significant issues in Internet of Things (IoT) cloud computing is scheduling tasks. Recent developments in IoT-based technologies have led to a meteoric rise in the demand for cloud storage. In order to load the IoT services onto clou...
The effusive eruption at Mt. Fagradalsfjall began on 19 March 2021 and it ended a period of about 800 years of volcano dormancy on the Reykjanes Peninsula. To monitor and evaluate power output of the eruption, we compiled in total 254 freely availabl...
The diameter of the sunflower flower head and the thickness of its margins are important crop phenotypic parameters. Traditional, single-dimensional two-dimensional imaging methods often struggle to balance precision with computational efficiency. Th...
To address fragile feature representation in sparse regions and detail loss in occluded scenes caused by uneven sampling density in 3D point cloud semantic segmentation on the SemanticKITTI dataset, this article proposes an innovative framework that...
With the integrated development of the Internet, wireless sensor technology, cloud computing, and mobile Internet, there has been a lot of attention given to research about and applications of the Internet of Things. A Wireless Sensor Network (WSN) i...
Data in multi-tenant cloud environments is increasingly shared across organizations, making strong in-memory isolation a critical requirement. Existing confidential computing mechanisms such as AMD SEV provide hardware-enforced protection, but they r...
The classification of point clouds is a basic task in airborne laser scanning (ALS) point cloud processing. It is quite a challenge when facing complex observed scenes and irregular point distributions. In order to reduce the computational burden of...
Tomography aims to recover a three-dimensional (3D) density map of a medium or an object. In medical imaging, it is extensively used for diagnostics via X-ray computed tomography (CT). We define and derive a tomography of cloud droplet distributions...
3D LiDAR has become an indispensable sensor in autonomous driving vehicles. In LiDAR-based 3D point cloud semantic segmentation, most voxel-based 3D segmentors cannot efficiently capture large amounts of context information, resulting in limited rece...
Accurate and timely mapping of paddy rice cultivation areas underpins food security assessment, agricultural resource management, and climate change adaptation. Because remote sensing provides repeated, large-scale observations, it has become indispe...
Technological innovations in the hardware of RGB-D sensors have allowed the acquisition of 3D point clouds in real time. Consequently, various applications have arisen related to the 3D world, which are receiving increasing attention from researchers...
Surface defects in magnetic tiles pose significant challenges to the performance and reliability of permanent magnet motors. Traditional defect detection methods, including visual inspection and 2D imaging, are limited by subjectivity, resolution con...
Droughts have a significant impact on surface water resources, especially in arid and semi-arid regions. Computational and data handling limitations have constrained previous time-series analyses. However, advances in cloud computing services and rem...
To address the challenge of measuring the plate wall offset at the U-shaped groove positions after assembling large cylindrical shell arc segments, this paper proposes a measurement method based on multi-line-structured light vision sensors. The sens...
This article presents AgriExp, a remote-based workflow for the rapid mapping and monitoring of archaeological and cultural heritage locations endangered by new agricultural expansion and encroachment. Our approach is powered by the cloud-computing da...
3D sonar is the primary technical means for the detection and health assessment of underwater structures. However, due to the harsh constraints of underwater imaging conditions, these point clouds experience severe noise interference and inconspicuou...
The increasing adoption of Internet of Things devices has led to a significant demand for cloud services, where latency and bandwidth play a crucial role in shaping users’ perception of network service quality. However, the use of cloud service...
Various classification methods have been developed to extract meaningful information from Airborne Laser Scanner (ALS) point clouds. However, the accuracy and the computational efficiency of the existing methods need to be improved, especially for th...
Rice is one of the most important staple crops in China, and the rapid and accurate extraction of rice planting areas plays a crucial role in the agricultural management and food security assessment. However, the existing rice field identification me...
The automated reconstruction of Building Information Modeling (BIM) objects from point cloud data is still subject of ongoing research. A vital step in the process is identifying the observations for each wall object. Given a set of segmented and cla...
In cloud computing, multi-tenant shared storage is widely used for efficiency. ZNS SSDs have become a popular choice due to their high throughput and low latency. However, they still face challenges: the zone structure is not exposed to tenants, maki...
Research on extracting building from airborne point clouds is abundant, yet discussions regarding scenarios where vegetation and building structures are closely intertwined with similar height in rural areas remain relatively scarce. This thesis adop...
Deep-learning techniques have significantly improved object detection performance, especially with binocular images in 3D scenarios. To supervise the depth information in stereo 3D object detection, reconstructing the 3D dense depth of LiDAR point cl...
Based on the theory of computational fluid dynamics (CFD), with the help of the Fluent software and the powerful parallel computing capability of the super cloud computer, the single-phase flow transient simulation calculation of the windage power lo...
Accurate registration of multi-temporal LiDAR point clouds is essential for reliable monitoring of mining subsidence. Systematic errors in point clouds acquired at different times can arise from GNSS/INS positioning drift, sensor calibration bias, an...
Crop classification is an important remote sensing task with many applications, e.g., food security monitoring, ecosystem service mapping, climate change impact assessment, etc. This work focuses on mapping 10 crop types at the field level in an agri...
This paper presents next-generation mapping of plant ecological communities including land cover and agricultural types at 10 m spatial resolution countrywide. This research introduces modelling and mapping of land cover and ecological communities se...
Unmanned aerial vehicle (UAV) collaboration has become the main means of indoor and outdoor regional search, railway patrol, and other tasks, and navigation planning is one of the key, albeit difficult, technologies. The purpose of UAV navigation pla...
Mapping surface water over time provides the spatially explicit information essential for hydroclimatic research focused on droughts and flooding. Hazard risk assessments and water management planning also rely on accurate, long-term measurements des...
The primary objective of this paper is the automation of the point cloud georeferencing process through the algorithmic localization of various control point types and the subsequent calculation of transformation parameters. The proposed approach uti...
Gas-insulated transmission lines (GILs) are increasingly deployed in dense urban power networks, where complex construction activities may introduce external mechanical impacts and pose risks to pipeline structural integrity. However, existing GIL mo...
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