作者:
Hu, YingyiZhang, LingChinese Acad Sci
Northwest Inst Ecoenvironm & Resources Key Lab Cryospher Sci & Frozen Soil Engn Heihe Remote Sensing Expt Res Stn Lanzhou 730000 Peoples R China Jiangsu Ocean Univ
Sch Marine Technol & Geomat Lianyungang 222005 Jiangsu Peoples R China
Data-fusion techniques leverage the strengths of multisource precipitation data and can significantly enhance the accuracy of precipitation estimates. However, the extent to which these techniques improve precipitatio...
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Data-fusion techniques leverage the strengths of multisource precipitation data and can significantly enhance the accuracy of precipitation estimates. However, the extent to which these techniques improve precipitation estimates (i.e., added value) compared to interpolation algorithms and the factors driving this improvement remain unclear. To address these gaps, this study compared the performance of two merging techniques, i.e., double machine learning (DML) and geographically weighted regression (GWR), with multiple interpolation algorithms in estimating precipitation across China. The interpolation algorithms vary in complexity and include typical methods (IDW and Kriging), semi-physical methods (GIDS, DAYMET, and MicroMet), and climatologically aided interpolation (CAI). We quantified the added value of the merging techniques over these interpolation algorithms and investigated the driving factors using a data-driven approach. Results indicate that the merging techniques outperform all the interpolation algorithms, regardless of their complexity. The merging techniques provide greater added value in gauge-scarce regions (e.g., Northeast China) than in gauge-rich regions (e.g., Northwest China). The magnitude of the added value from merging techniques is significantly influenced by the choice of interpolation algorithms due to their varying performance. Additionally, our data-driven model reveals that factors such as the amount of precipitation, number of wet days, performance of precipitation products, and gauge density are key drivers that negatively affect the added value of merging techniques. This study highlights the importance of integrating multisource data to improve precipitation estimates, especially in regions with sparse gauges, rather than relying solely on gauge-only interpolation.
This paper presents a quantitative comparison of several widely used interpolation algorithms, i.e., Ordinary Kriging (OrK), Universal Kriging (UnK), planar fit and Inverse Distance Weighting (IDW), based on a grid-ba...
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This paper presents a quantitative comparison of several widely used interpolation algorithms, i.e., Ordinary Kriging (OrK), Universal Kriging (UnK), planar fit and Inverse Distance Weighting (IDW), based on a grid-based single-shell ionosphere model over China. The experimental data were collected from the Crustal Movement Observation Network of China (CMONOC) and the International GNSS Service (IGS), covering the days of year 60-90 in 2015. The quality of these interpolation algorithms was assessed by cross-validation in terms of both the ionospheric correction performance and Single-Frequency (SF) Precise Point Positioning (PPP) accuracy on an epoch-by-epoch basis. The results indicate that the interpolation models perform better at mid-latitudes than low latitudes. For the China region, the performance of OrK and UnK is relatively better than the planar fit and IDW model for estimating ionospheric delay and positioning. In addition, the computational efficiencies of the IDW and planar fit models are better than those of OrK and UnK.
Computationally simple algorithms are proposed to estimate the local frequency vector of a real two-dimensional signal with slowly varying parameters in the presence of additive Gaussian noise. The rough most likely e...
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Computationally simple algorithms are proposed to estimate the local frequency vector of a real two-dimensional signal with slowly varying parameters in the presence of additive Gaussian noise. The rough most likely estimate of the frequency vector is refined using three-point interpolation algorithms and the singular value decomposition of a 3 x 3 matrix of discrete Fourier transform coefficients. The results of computer simulation are presented showing the efficiency of the algorithms for analyzed fragments of small size.
Image interpolation is a key technique of image super-resolution. Four two dimensional (2-D) autoregressive (AR) modeling-based image interpolation algorithms have been reported to have better performance in edge and ...
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ISBN:
(纸本)9781538619377
Image interpolation is a key technique of image super-resolution. Four two dimensional (2-D) autoregressive (AR) modeling-based image interpolation algorithms have been reported to have better performance in edge and texture preservation than conventional image polynomial interpolation algorithms. However, there is lack of performance comparison among them. For super-resolution reconstruction quality, this paper is going to fill up the gap by a comparison study on the four 2-D AR modeling-based interpolation methods: novel edge-directed interpolation (NEDI), soft-decision adaptive interpolation (SAI), sparse representation interpolation with nonlocal autoregressive modeling (SR-NARM), and adaptive super-pixel-guided AR modeling (ASARM). Furthermore, the four interpolation algorithms are compared in the light of peak signal to noise ratio, feature similarity index, mean squared error and structural similarity index. From comparative results we observe that ASARM method has relatively better performance than other three methods but is more time-consuming than the NEDI and SAI methods.
Majority of contemporary spatial information systems allow generation and visualization of the digital terrain model based on GRID type of the regular squares network. The values at nodal points for such a GRID are in...
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Majority of contemporary spatial information systems allow generation and visualization of the digital terrain model based on GRID type of the regular squares network. The values at nodal points for such a GRID are in most cases computed by one of the many available interpolation methods on the basis of dispersed measurement points. The commonly used solutions allow in most cases application of a selected interpolation method in a global way within the entire analyzed area, which does not secure the same accuracy of surface generated. The paper describes generation of a digital terrain model by applying a combination of interpolation methods. The criterion of method choice was dependent on the dispersion of measurement points around the GRID node. This solution allows successive complementing the resultant set of computed set with values determined with a specific error and as a result improves the accuracy of the model generated. (C) 2013 Elsevier Ltd. All rights reserved.
In this paper two iterative interpolation algorithms proposed in the scientific literature for estimating the frequency of complex-valued sine-waves are generalized to a generic Maximum Sidelobe Decay (MSD) window in ...
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ISBN:
(纸本)9781479972678
In this paper two iterative interpolation algorithms proposed in the scientific literature for estimating the frequency of complex-valued sine-waves are generalized to a generic Maximum Sidelobe Decay (MSD) window in order to achieve highly accurate estimates even when real-valued pure or harmonically distorted sine-waves are analyzed. The analytical expressions for the frequency estimations formulas are derived. Moreover the accuracy achieved when pure, noisy, and noisy and harmonically distorted sine-waves are analyzed is compared with those provided by the classical Interpolated Discrete Fourier Transform (IpDFT) and three-point IpDFT algorithms through computer simulations. The performed comparison allows us to determine in which situations the proposed algorithms can be advantageously used.
Gramophone records were the main recording medium for half a century and regained widespread popularity over the past couple of years. Being an analogue storage medium, vinyl records are subject to distortions caused ...
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ISBN:
(纸本)9781479928668
Gramophone records were the main recording medium for half a century and regained widespread popularity over the past couple of years. Being an analogue storage medium, vinyl records are subject to distortions caused by scratches, dust, high temperatures and extensive playback. This paper discusses a number of well-known interpolation algorithms that can be used to reduce the noise by reconstructing the distorted gaps, which include the nearest neighbour, cosine, polynomial, spline, Hermite and Fourier interpolation. The reconstruction accuracy of these algorithms were determined by using a large dataset of songs from eight different music genres. It was found that cosine and polynomial interpolation have the best mean performance with regards to reconstruction accuracy and execution time. It was also found that certain genres can be easier reconstructed than others.
The goal of multiple-image hiding is to hide several secret images within another carrier image without significantly changing its appearance, and then perfectly reconstruct all of the secret images. The challenge is ...
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The goal of multiple-image hiding is to hide several secret images within another carrier image without significantly changing its appearance, and then perfectly reconstruct all of the secret images. The challenge is to ensure that the stego-image has great visual quality and can resist various steganalysis under the premise of hiding as much information as possible in one image. To address this issue, the majority of known image-hiding methods focus on hiding images using compression techniques. In this article, we present a novel multiple-image hiding method based on up-sampling and reversible color transformation. First, the interpolation algorithm up-samples the carrier image, so that the attribute of similar neighboring pixel values in the up-sampled image can significantly improve the effect of image hiding. The embedding procedure is then performed using the proposed Euclidean Distance (ED)-based block matching and reversible color transformation, which decreases the chance of local blurring in the stego-image. Experimental results show that the proposed method surpasses existing advanced methods by achieving an average of 33 dB and 28 dB of PSNR for the stego-image with a hiding capacity 2 BPP and 8 BPP, and obtaining 100% reconstructing accuracy for all secret images. It also has a high level of resistance to steganalysis and a strong robustness against various image-processing attacks.
This paper presents the design, implementation, and experimental validation of a novel canned cycle for CNC milling machines, enabling the precise and efficient cutting of threads with fixed or variable pitch and radi...
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This paper presents the design, implementation, and experimental validation of a novel canned cycle for CNC milling machines, enabling the precise and efficient cutting of threads with fixed or variable pitch and radius. Conventional canned cycles are limited to fixed pitch threads, restricting the versatility of CNC milling machines in thread machining *** development process involves integrating a sophisticated control algorithm into the CNC milling machine's software, giving the operator remarkable control over the thread cutting process. This algorithm allows the operator to choose between external or internal threads, set both initial and final radii, determine initial and final pitches, specify the number of turns, and select the left or right-hand thread type. Such flexibility enables the creation of threads with diverse geometries. Furthermore, the proposed canned cycle provides the capability to switch between roughing and finishing passes by adjusting the step motion along the prescribed helical *** tests conducted under various threading cases clearly demonstrate the efficiency of the proposed canned cycle. These results showcase its capability to address a wide range of machining scenarios, offering practical solutions applicable across a spectrum of applications.
This paper presents the development of a new canned cycle for CNC milling machines capable of cutting threads with variable pitch, addressing a significant limitation in modern CNC systems. While existing CNC milling ...
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This paper presents the development of a new canned cycle for CNC milling machines capable of cutting threads with variable pitch, addressing a significant limitation in modern CNC systems. While existing CNC milling machines provide canned cycles for thread cutting, they lack the capability to program variable pitch, necessitating reliance on CAM systems. In response, the proposed canned cycle offers increased flexibility, quicker setup times, and reduced dependence on CAM systems. The cycle accommodates both internal and external threads, supports left-hand or right-hand threading, and incorporates a user-friendly control panel for easy programming. To validate its efficiency, the canned cycle is implemented using a G-code parametric algorithm, and a series of simulation tests are conducted. The results demonstrate the viability and advantages of the new CNC milling feature in cutting threads with variable pitch, opening up possibilities for various mechanical applications.
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