The evaluation of the shrinkage–swelling characteristic of expansive clay is of great significance, but it is a complex problem since the evaluation process involves numerous uncertain factors, such as randomness, non-subordination, and hesitat...
Determining the projection direction vector (PDV) is essential to the projection pursuit evaluation method for high-dimensional problems under multiple uncertainties. Although the PP method using a cloud model can facilitate interpretation of the fuz...
In this paper, a statistical cloud model was proposed for optimal design of the proportional integral derivative (PID) controllers used in current control of vehicle-to-grid connected inverter systems with PID parameters. By collecting the effective...
The evaluation of land eco-security is challenging because it is involved with various uncertainty factors. Although the normal cloud model provides an idea for dealing with the randomness and fuzziness of indicators for the evaluation of land eco-se...
The Cloud-Based Secured Connection Management Model (CS-CMM) for high-density fog networks is a novel approach that leverages cloud resources and the proliferation of computing power at the edge of networks. The model seeks to address the challenges...
The three-dimensional (3D) reconstruction of buildings using photogrammetric point clouds is important for many applications, ranging from digital city construction to urban energy consumption analysis. However, problems such as building complexity a...
Automatic vehicle extraction from an airborne laser scanning (ALS) point cloud is very useful for many applications, such as digital elevation model generation and 3D building reconstruction. In this article, an object-based point cloud analysis (OBP...
Discontinuity trace provides critical geological data for engineering design and construction optimization. However, current extraction methods relying on discontinuity intersection fitting are highly sensitive to the segmentation accuracy of individ...
Urban Waterlogging Susceptibility Assessment (UWSA) is vital for resilient urban planning and disaster preparedness. Conventional methods depend heavily on Historical Waterlogging Records (HWR), which are limited by their reliance on extreme rainfall...
As threat vectors and adversarial capabilities evolve, Cloud-Assisted Connected and Autonomous Vehicles (CCAVs) are becoming more vulnerable to cyberattacks. Several established threat analysis and risk assessment (TARA) methodologies are publicly av...
The safety risk evaluation of foundation pit excavations in metro stations involves multiple factors with randomness and fuzziness. This study improves the Second Improved CRITIC-Cloud Model for more precise risk assessment. The approach integrates c...
Two-meter-scale true-triaxial hydraulic-fracturing models involve a large monitoring volume, strongly nonuniform microseismic event densities, and substantial vibration and background noise, making conventional fixed-scale clustering or direct geomet...
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 study proposes the adoption of the IoT technology for the home monitoring of the health status of frail patients. Such a solution is thought to be part of the forthcoming Italian COT; the latter is an organizational model which is devoted to int...
With the high proportion of wind and photovoltaic (PV) power connection in the new electricity system, the system output power volatility is enhanced. When the output fluctuation of the system is suppressed, the pumped storage condition is changed fr...
This paper proposes a novel method to reconstruct hierarchical 3D tree models from Mobile Laser Scanning (MLS) point clouds. Starting with a neighborhood graph from the tree point clouds, the method treats the root point of the tree as a source point...
In this paper, aiming at the problem of poor quality and low spraying efficiency of irregular for complex freeform surfaces, a new spray painting robot trajectory planning method based on point cloud slicing technology is proposed. Firstly, the point...
Clouds moving at a high speed in front of the Sun can cause step changes in the output power of photovoltaic (PV) power plants, which can lead to voltage fluctuations and stability problems in the connected electricity networks. These effects can be...
Connected vehicles are a vital part of smart cities, which connect over a wireless connection and bring mobile computation and communication abilities. As a mediator, fog computing resides between vehicles and the cloud and provides vehicles with pro...
With the advances in networking technologies, robots can use the almost unlimited resources of large data centers, overcoming the severe limitations imposed by onboard resources: this is the vision of Cloud Robotics. In this context, we present DewRO...
Cloud detection in remote sensing images is a crucial preprocessing step that efficiently identifies and extracts cloud-covered areas within the images, ensuring the precision and reliability of subsequent analyses and applications. Given the diversi...
Formulated as a pixel-level labeling task, data-driven neural segmentation models for cloud and corresponding shadow detection have achieved a promising accomplishment in remote sensing imagery processing. The limited capability of these methods to d...
Topological signal processing is emerging alongside Graph Signal Processing (GSP) in various applications, incorporating higher-order connectivity structures—such as faces—in addition to nodes and edges, for enriched connectivity modeling...
Solar irradiance is one of the main factors affecting the output of photovoltaic power stations. The cloud distribution above the photovoltaic power station can determine the strength of the absorbed solar irradiance. Cloud estimation is another impo...
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...
Photovoltaic power generation must be predicted to counter the system instability caused by an increasing number of photovoltaic power-plant connections. In this study, a method for predicting the cloud volume and power generation using satellite ima...
In the last decade, the developments in healthcare technologies have been increasing progressively in practice. Healthcare applications such as ECG monitoring, heartbeat analysis, and blood pressure control connect with external servers in a manner c...
Accurately reconstructing tree skeletons from multi-view images is challenging. While most existing works use skeletonization from 3D point clouds, thin branches with low-texture contrast often involve multi-view stereo (MVS) to produce noisy and fra...
Applications in the Internet of Things (IoT) context continuously generate large amounts of data. The data must be processed and monitored to allow rapid decision making. However, the wireless connection that links such devices to remote servers can...
Cloud detection is an important and difficult task in the pre-processing of satellite remote sensing data. The results of traditional cloud detection methods are often unsatisfactory in complex environments or the presence of various noise disturbanc...
Rapid and accurate identification of precipitation clouds from satellite observations is essential for the research of quantitative precipitation estimation and precipitation nowcasting. In this study, we proposed a novel Convolutional Neural Network...
Modern agriculture is increasingly challenged by the need for scalable, sustainable, and connectivity-resilient digital solutions. While existing smart farming platforms offer valuable insights, they often rely heavily on centralized cloud infrastruc...
Image classification usually requires connectivity and access to the cloud, which is often limited in many parts of the world, including hard-to-reach rural areas. Tiny machine learning (tinyML) aims to solve this problem by hosting artificial intell...
In the age of the Internet of Things (IoT), more and more sensors, actuators and smart devices get connected to the network. Application providers often combine this connectivity with novel scenarios involving cloud computing. Before implementing cha...
In this paper, a new semi-automatic procedure to transform three-dimensional point clouds of complex objects to three-dimensional finite element models is presented and validated. The procedure conceives of the point cloud as a stacking of point sect...
The connection of many devices has brought new challenges with respect to the centralized architecture of cloud computing. The fog environment is suitable for many services and applications for which cloud computing does not support these well, such...
The rapid expansion of IoT devices represents significant progress in areas such as smart buildings and smart cities, but at the same time, the volume of data generated represents a challenge, which can lead to real bottlenecks in the data analysis p...
With advancements in Earth observation capabilities, the demand for large-scale mapping using remote sensing images has increased significantly. However, selecting an optimal image set for the area of interest (AOI) from a large collection of remote...
This paper presents a new method for constructing quickly and automatically precision tree models from point clouds of the trunk and branches obtained by terrestrial laser scanning. The input of the method is a point cloud of a single tree scanned fr...
As interest in point cloud processing has gradually increased in the industry, point cloud sampling techniques have been researched to improve deep learning networks. As many conventional models use point clouds directly, the consideration of computa...
Three-dimensional indoor models have wide applications in fields such as indoor navigation, civil engineering, virtual reality, and so on. With the development of LiDAR technology, automatic reconstruction of indoor models from point clouds has gaine...
In dynamic and open cloud service processes, particularly in distributed networked manufacturing environments, the complex and volatile manufacturing landscape introduces numerous uncertainties and disturbances. This paper addresses the common issue...
The point cloud data from actual measurements are often sparse and incomplete, making it difficult to apply them directly to visual processing and 3D reconstruction. The point cloud completion task can predict missing parts based on a sparse and inco...
Federated learning (FL) has emerged as a powerful approach for privacy-preserving model training in autonomous vehicle networks, where real-world deployments rely on multiple roadside units (RSUs) serving heterogeneous clients with intermittent conne...
We present a fully automatic approach for reconstructing compact 3D building models from large-scale airborne point clouds. A major challenge of urban reconstruction from airborne LiDAR point clouds lies in that the vertical walls are typically missi...
Cloud-based services are growing more rapidly than ever, and so does the management challenge on their providers’ side. Cloud-based datacenter networks are built with nodes of huge processing power, connected by high bandwidth capacities to car...
Frontier large language models (LLMs) depend on energy-intensive cloud data centers and continuous connectivity that many low-resource healthcare settings lack. This paper investigates whether Low-Rank Adaptation (LoRA) fine-tuning combined with 4-bi...
Autonomous underwater vehicles (AUVs) have increasingly played a key role in monitoring the marine environment, studying its physical-chemical parameters for the supervision of endangered species. AUVs now include a power source and an intelligent co...
As for rock numerical calculation and stability analysis, it is essential to build a numerical model of rock mass with concise and accurate structure information through the three-dimensional surface reconstruction of rock-mass point clouds. However,...
A model for tracking objects whose topological properties change over time is proposed. Such changes include the splitting of an object into multiple objects or the merging of multiple objects into a single object. The proposed model employs a novel...
of 14