- 标题
- 摘要
- 关键词
- 实验方案
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Noise-robust transparent visualization of large-scale point clouds acquired by laser scanning
摘要： We propose a high-quality transparent visualization method suitable for large-scale laser-scanned point clouds. We call the method “stochastic point-based rendering (SPBR),” which is based on a novel stochastic algorithm. SPBR enables us to clearly observe the deep interior of laser-scanned 3D objects with the correct feeling of depth. The high quality of SPBR originates from the effect of “stochastic noise transparentization,” which is an effect to make the measurement noise transparent and invisible in the created images. We mathematically prove that this effect also makes the created transparent images coincide with the results of the conventional methods based on the alpha blending, which is time-consuming and impractical for large-scale laser-scanned point clouds. We also demonstrate the effectiveness of SPBR by applying it to modern buildings, cultural heritage objects, forests, and a factory. For all of the cases, the method works quite well, realizing clear and correct 3D see-through imaging of the laser-scanned objects.
关键词： High quality 3D see-through imaging,Laser-scanned point cloud,Large-scale data,Stochastic noise transparentization,Visualization
更新于2025-09-23 15:21:01
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An On-Line Low-Cost Irradiance Monitoring Network with Sub-Second Sampling Adapted to Small-Scale PV Systems
摘要： Very short-term solar forecasts are gaining interest for their application on real-time control of photovoltaic systems. These forecasts are intimately related to the cloud motion that produce variations of the irradiance field on scales of seconds and meters, thus particularly impacting in small photovoltaic systems. Very short-term forecast models must be supported by updated information of the local irradiance field, and solar sensor networks are positioning as the more direct way to obtain these data. The development of solar sensor networks adapted to small-scale systems as microgrids is subject to specific requirements: high updating frequency, high density of measurement points and low investment. This paper proposes a wireless sensor network able to provide snapshots of the irradiance field with an updating frequency of 2 Hz. The network comprised 16 motes regularly distributed over an area of 15 m × 15 m (4 motes × 4 motes, minimum intersensor distance of 5 m). The irradiance values were estimated from illuminance measurements acquired by lux-meters in the network motes. The estimated irradiances were validated with measurements of a secondary standard pyranometer obtaining a mean absolute error of 24.4 W/m2 and a standard deviation of 36.1 W/m2. The network was able to capture the cloud motion and the main features of the irradiance field even with the reduced dimensions of the monitoring area. These results and the low-cost of the measurement devices indicate that this concept of solar sensor networks would be appropriate not only for photovoltaic plants in the range of MW, but also for smaller systems such as the ones installed in microgrids.
关键词： pyranometer,irradiance monitoring network,very short-term solar forecasting,microgrids,cloud enhancement,wireless sensor network,lux-meter
更新于2025-09-23 15:21:01
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[IEEE 2018 20th International Conference on Transparent Optical Networks (ICTON) - Bucharest (2018.7.1-2018.7.5)] 2018 20th International Conference on Transparent Optical Networks (ICTON) - Planning of Geo-Distributed Cloud Data Centers in Fast Developing Economies
摘要： In recent years, with the rapid development of big data, artificial intelligence and cloud computing, the construction of cloud data centers has entered into a fast-growing period, especially in fast developing economies. The placement for geo-distributed cloud data centers has a great impact on costs and performance. In this paper, we propose a framework to determine the optimal placement of geo-distributed cloud data centers, taking into considering both cost minimization and network performance. In we apply this framework to the placement to cloud data centers in China. We show how the DC placement may be affected by network performance requirements. We also show how factors like population mobility and adoption of clean energy, typical in fast developing economies, may affect DC placement. We research provides insights to the long term DC planning in fast developing economies.
关键词： network performance,fast developing economies,geo-distributed cloud data centers,cost minimization
更新于2025-09-23 15:21:01
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Combination of sequential cloud point extraction and hydride generation atomic fluorescence spectrometry for preconcentration and determination of inorganic and methyl mercury in water samples
摘要： A sequential cloud point extraction method was established for the determination of trace mercury species in water samples by hydride generation atomic fluorescence spectrometry (HGAFS). The proposed extraction system consisted of two chief steps: isolation of inorganic mercury (Hg2+) by chelating with potassium?iodide and methyl green, and then isolation of methyl mercury (CH3Hg+) by chelating with ammonium pyrrolidinedithiocarbamate. The nonionic surfactant Triton X?114 was chosen as the extractant, while the brominating agent was applied to convert extracted CH3Hg+ into Hg2+. Before HGAFS detection, the two surfactant?rich phases obtained in the sequential process were separately diluted to 3 mL with 5% (v/v) HCl after the addition of antifoam (0.4 mL). The effects of experimental conditions, including pH and concentration of surfactant and chelating agents, on cloud point extraction were optimized. Under the optimum conditions, the limits of detection for Hg2+ and CH3Hg+ were 0.007 and 0.018 μg/L with the enrichment factors of 15.1 and 11.2, respectively. The proposed method was successfully used for the determination of trace Hg2+ and CH3Hg+ in water samples with satisfactory recoveries of 95?104%.
关键词： Hydride generation atomic fluorescence spectrometry,Non?chromatographic mercury speciation,Cloud point extraction
更新于2025-09-23 15:21:01
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Fusion of Multitemporal LiDAR Data for Individual Tree Crown Parameter Estimation on Low Density Point Clouds
摘要： The increasingly availability of Light Detection and Ranging (LiDAR) data acquired at different times can be used to analyze the forest dynamics at individual tree level. This often requires to deal with LiDAR point clouds having significantly different point densities. To address this issue, this paper presents a method for the fusion of multitemporal LiDAR data which aims at using the information provided by high density LiDAR data (higher than 10 pts/m2) to improve the single tree parameter estimation of low density data (up to 5 pts/m2) acquired over the same forest at different times. The method first accurately characterizes the crown shapes on the high density data. Then, it uses the obtained estimates to drive the tree parameter estimation on the low density LiDAR data. The method has been tested on a multitemporal dataset acquired in coniferous forests located in the Italian Alps. Experimental results confirmed the effectiveness of the method.
关键词： Point Cloud,Tree Crown Parameters,Remote Sensing,Multitemporal LiDAR Data,Data Fusion
更新于2025-09-23 15:21:01
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Cloud Detection in Satellite Images Based on Natural Scene Statistics and Gabor Features
摘要： Cloud detection is an important task in remote sensing (RS) image processing. Numerous cloud detection algorithms have been developed. However, most existing methods suffer from the weakness of omitting small and thin clouds, and from an inability to discriminate clouds from photometrically similar regions, such as buildings and snow. Here, we derive a novel cloud detection algorithm for optical RS images, whereby test images are separated into three classes: thick clouds, thin clouds, and noncloudy. First, a simple linear iterative clustering algorithm is adopted that is able to segment potential clouds, including small clouds. Then, a natural scene statistics model is applied to the superpixels to distinguish between clouds and surface buildings. Finally, Gabor features are computed within each superpixel and a support vector machine is used to distinguish clouds from snow regions. The experimental results indicate that the proposed model outperforms state-of-the-art methods for cloud detection.
关键词： natural scene statistics (NSS),support vector machine (SVM),Gabor feature,superpixel,Cloud detection
更新于2025-09-23 15:21:01
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Handbook of Exoplanets || Exoplanet Atmosphere Measurements from Transmission Spectroscopy and Other Planet Star Combined Light Observations
摘要： It is possible to learn a great deal about exoplanet atmospheres even when we cannot spatially resolve the planets from their host stars. In this chapter, we overview the basic techniques used to characterize transiting exoplanets – transmission spectroscopy, emission and re?ection spectroscopy, and full-orbit phase curve observations. We discuss practical considerations, including current and future observing facilities and best practices for measuring precise spectra. We also highlight major observational results on the chemistry, climate, and cloud properties of exoplanets.
关键词： Observing facilities,Transmission spectroscopy,Emission spectroscopy,Climate,Re?ection spectroscopy,Cloud properties,Exoplanet atmospheres,Phase curve observations,Atmospheric chemistry
更新于2025-09-23 15:21:01
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Cloud Masking Technique for High-Resolution Satellite Data: An Artificial Neural Network Classifier Using Spectral & Textural Context
摘要： Cloud masking is a very important application in remote sensing and an essential pre-processing step for any information derivation applications. It helps in estimation of usable portion of the images. Many popular spectral classi?cation techniques rely upon the presence of a short-wave infrared band or bands of even higher wavelength to differentiate between clouds and other land covers. However, these methods are limited to sensors equipped with higher wavelength bands. In this paper, a generic and ef?cient technique is attempted using the Cartosat-2 series (C2S) satellite which is having high-resolution multispectral sensor in the visible and near-infrared bands. The methodology is based on textural features from the available spectral context, and using a feedforward neural network for the classi?cation is proposed. The method was shown to have an overall accuracy of 97.98% for a large manually pre-classi?ed validation dataset with more than 2 million data points. Experimental results and cloud masks generated for various scenes show that the method may be viable as a reasonable cloud masking algorithm for C2S data.
关键词： Cloud masking,Feed forward network,High-resolution satellite data,Image classi?cation,Arti?cial neural network,GLCM texture
更新于2025-09-23 15:21:01
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[IEEE 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) - Miyazaki, Japan (2018.10.7-2018.10.10)] 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) - Laser Variational Autoencoder for Map Construction and Self-Localization
摘要： In this paper, a vehicular cloud (VC) model is adopted where vehicles offer data as a service. We propose solutions for efficient data delivery based on transmission scheduling methods where vehicles gather data from their mounted sensors. This is done by first organizing vehicles into clusters, so that each cluster works as VC. A distributed D-hop cluster formation algorithm is presented to dynamically form vehicle clouds. The algorithm groups vehicles into non-overlapping clusters, which have adaptive sizes according to their mobility. VCs are created in such a way that each vehicle is at most D-hops away from a cloud coordinator (broker). Each vehicle chooses its broker based on relative mobility calculations within its D-hop neighbors. After cloud construction, a mathematical optimization scheduling algorithm is used to maximize throughput and minimize delay in delivering data from vehicles to their VC broker. Our proposed optimization model implements a contention-free-based medium access control where physical conditions of the channel are fully analyzed. Extensive simulations were performed for different scenarios to evaluate the performance of the proposed cloud formation and cloud-based transmission scheduling algorithms. Results show that VCs formed by our algorithms are more stable and provide higher data throughputs compared with others.
关键词： vehicular cloud,transmission scheduling,Cloud formation,optimization,VANET
更新于2025-09-23 15:19:57
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[IEEE 2019 Electric Power Quality and Supply Reliability Conference (PQ) & 2019 Symposium on Electrical Engineering and Mechatronics (SEEM) - K?¤rdla, Estonia (2019.6.12-2019.6.15)] 2019 Electric Power Quality and Supply Reliability Conference (PQ) & 2019 Symposium on Electrical Engineering and Mechatronics (SEEM) - Impact of LED Thermal Stability to Household Lighting Harmonic Load Current Modeling
摘要： This paper focuses on energy efficiency aspects and related benefits of radio-access-network-as-a-service (RANaaS) implementation (using commodity hardware) as architectural evolution of LTE-advanced networks toward 5G infrastructure. RANaaS is a novel concept introduced recently, which enables the partial centralization of RAN functionalities depending on the actual needs as well as on network characteristics. In the view of future definition of 5G systems, this cloud-based design is an important solution in terms of efficient usage of network resources. The aim of this paper is to give a vision of the advantages of the RANaaS, to present its benefits in terms of energy efficiency and to propose a consistent system-level power model as a reference for assessing innovative functionalities toward 5G systems. The incremental benefits through the years are also discussed in perspective, by considering technological evolution of IT platforms and the increasing matching between their capabilities and the need for progressive virtualization of RAN functionalities. The description is complemented by an exemplary evaluation in terms of energy efficiency, analyzing the achievable gains associated with the RANaaS paradigm.
关键词： power model,radio access networks,RAN-as-a-service,LTE-advanced,5G,wireless communication,cloud-RAN,Energy efficiency
更新于2025-09-23 15:19:57