Alpine wetlands are a special ecosystem that is extremely sensitive to global climate change. The unique geographical location and climatic conditions of the Yellow-River-Source National Park give rise to diverse wetl...
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Alpine wetlands are a special ecosystem that is extremely sensitive to global climate change. The unique geographical location and climatic conditions of the Yellow-River-Source National Park give rise to diverse wetland types at the land-water interface, which exhibit phenomena such as "same object with different spectra" and "different objects with the same spectrum." These complexities pose significant challenges in accurately extracting information from alpine wetlands in the study area. To address these challenges, this study proposes a novel integrated multialgorithm feature optimization model that combines three filtering algorithms with a random forest (RF) algorithm for classifying alpine wetland information. First, the rich feature information in the image is initially filtered using a fusion of the three algorithms. Then, the RF algorithm is applied to optimize the filtered features. Finally, the RF classification model is used to refine wetland extraction based on this optimized feature set. The results show that 1) the fused filtering algorithm demonstrates higher stability than each individual algorithm and takes into consideration the strengths and weaknesses of each individual algorithm;2) the classification accuracy of the RF algorithm reaches its highest value when the number of feature variables is 21;3) the optimal classification of alpine wetlands is achieved using the RF classification model based on the best set of feature variables, resulting in an overall accuracy of 93.32% and a Kappa coefficient of 91.65% . Compared to existing land cover datasets, the proposed method provides a more detailed classification of alpine wetlands.
In order to locate historical traces, drone-based Laserscanning has become increasingly popular in archaeological prospection and historical conflict landscapes research. The low resolution of aircraft-based Laserscan...
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In order to locate historical traces, drone-based Laserscanning has become increasingly popular in archaeological prospection and historical conflict landscapes research. The low resolution of aircraft-based Laserscanning is not suitable for small-scale detailed analysis so that high-resolution UAV-based LiDAR data are required. However, many of the existing studies lack a systematic approach to UAV-LiDAR data acquisition and point cloud filtering. We use this methodology to detect anthropogenic terrain anomalies. In this study, we systematically investigated different influencing factors on UAV-LiDAR data acquisition. The flight parameters speed and altitude above ground were systematically varied. In addition, different vegetation cover and seasonal acquisition times were compared, and we evaluated three different types of filter algorithms to separate ground from non-ground. It could be seen from our experiments that for the detection of subsurface anomalies in treeless open terrain, higher flight speeds like 6 m/s were feasible. Regarding the flight altitude, we recommend an altitude of 50-75 m above ground. At higher flight altitudes of 100-120 m above ground, there is the risk that terrain characteristics smaller than 50 cm will be missed. Areas covered with deciduous forest should only be surveyed during leaf-off season. In the presence of low-level vegetation (small bushes and shrubs with a height of up to 2 m), it turned out that the morphological filter was the most suitable. In tree-covered areas with total absence of near ground vegetation, however, the choice of filter algorithm plays only a subordinate role, especially during winter where the resulting ground point densities have a percentage deviation of less than 6% from each other.
Research results are presented regarding the online derivation of temperature state space models for air cooled data centre rooms. Using exclusively real time temperature measurements from indoor sensors, filter algor...
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Research results are presented regarding the online derivation of temperature state space models for air cooled data centre rooms. Using exclusively real time temperature measurements from indoor sensors, filter algorithms are programmed for the numerical computation of the parameters of discrete time varying state space models. These control oriented models are adaptive and can predict the temperature distribution across data centre rooms where air-conditioning units are used to compensate heat loads generated by the computing equipment. The research has been conducted for the European Union project GENiC and the adopted approach has been tested and validated on a real data centre facility.
For experiments with high arrival rates, reliable identification of nearly-coincident events can be crucial. For calorimetric measurements to directly measure the neutrino mass such as HOLMES, unidentified pulse pile-...
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For experiments with high arrival rates, reliable identification of nearly-coincident events can be crucial. For calorimetric measurements to directly measure the neutrino mass such as HOLMES, unidentified pulse pile-ups are expected to be a leading source of experimental error. Although Wiener filtering can be used to recognize pile-up, it suffers from errors due to pulse shape variation from detector nonlinearity, readout dependence on subsample arrival times, and stability issues from the ill-posed deconvolution problem of recovering Dirac delta-functions from smooth data. Due to these factors, we have developed a processing method that exploits singular value decomposition to (1) separate single-pulse records from piled-up records in training data and (2) construct a model of single-pulse records that accounts for varying pulse shape with amplitude, arrival time, and baseline level, suitable for detecting nearly-coincident events. We show that the resulting processing advances can reduce the required performance specifications of the detectors and readout system or, equivalently, enable larger sensor arrays and better constraints on the neutrino mass.
The quality of surface finishing of manufactured parts is influenced by material and texture of the cutting edge as well as cutting parameters. To characterize the surface texture of a cutting tool standardized statis...
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The quality of surface finishing of manufactured parts is influenced by material and texture of the cutting edge as well as cutting parameters. To characterize the surface texture of a cutting tool standardized statistical roughness parameters are used as provided by inspection tools, i.e. profilers and microscopes. A topography scan undergoes several data analysis steps to detrend roughness from waviness and form before the standardized procedures (ISO 4287 and ISO 13565-2) are applied to estimate the statistical parameters of the roughness profile. A new series of ISO-standards (16610-xx) has been developed during the past decade that provide besides the Gaussian filtration method alternative filter algorithms. Each filter has a different kernel characteristics delivering slightly different curvatures of the waviness profile. This article shows the influence of the shape of filter kernels on roughness parameters and investigates possible estimation of the uncertainty of roughness amplitude density distributions accordingly. The filtration dependence of roughness parameters will be illustrated for a typical cutting tool, as example one of uncoated carbide. (C) 2016 The Authors. Published by Elsevier B.V.
The quality of surface finishing of manufactured parts is influenced by material and texture of the cutting edge as well as cutting parameters. To characterize the surface texture of a cutting tool standardized statis...
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The quality of surface finishing of manufactured parts is influenced by material and texture of the cutting edge as well as cutting parameters. To characterize the surface texture of a cutting tool standardized statistical roughness parameters are used as provided by inspection tools, i.e. profilers and microscopes. A topography scan undergoes several data analysis steps to detrend roughness from waviness and form before the standardized procedures (ISO 4287 and ISO 13565-2) are applied to estimate the statistical parameters of the roughness profile. A new series of ISO-standards (16610-xx) has been developed during the past decade that provide besides the Gaussian filtration method alternative filter algorithms. Each filter has a different kernel characteristics delivering slightly different curvatures of the waviness profile. This article shows the influence of the shape of filter kernels on roughness parameters and investigates possible estimation of the uncertainty of roughness amplitude density distributions accordingly. The filtration dependence of roughness parameters will be illustrated for a typical cutting tool, as example one of uncoated carbide.
The paper proposed dynamic direct heart rate algorithms in wearable device. Green light LED to direct heart rate is very popular in recent years which used analogy signal feedback to microcontroller calculation. Howev...
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ISBN:
(纸本)9781479985623
The paper proposed dynamic direct heart rate algorithms in wearable device. Green light LED to direct heart rate is very popular in recent years which used analogy signal feedback to microcontroller calculation. However, the different person physical signals are independent that including body fat, physical color, blood concentrations and oxygen concentration to influence observer data. Moreover, the body shock influence reflection feedback signal. This paper proposed automatic initial detect process and dynamic direct heart rate filter algorithms to process feedback analogy error noise. We presented a low cost solution for Texas Instruments AFE4403 heart rate oximeters with MSP430G2553 microcontroller to monitors body heart rate in wearable device. MSP430G2553 only have 512 byte RAM and 8k flash memory, so that the digital process calculation is an important topic. Finally, the experimental results show the dynamic algorithm has satisfactory performance.
Novel research results subject to the generation of agile numerical models for a real electric power plant are presented in this paper. Using only instrument measurements of various variables located in different part...
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Novel research results subject to the generation of agile numerical models for a real electric power plant are presented in this paper. Using only instrument measurements of various variables located in different parts of the power station, filtering algorithms are programmed for the computation of numerical models that describe system operation and are agile to adapt between different operational regimes. The contents of the paper constitute original industrial research conducted to a real electric power generation facility. The presented results were validated on site by the power plant's chief engineers. (C) 2014 Elsevier Ltd. All rights reserved.
The paper proposed dynamic direct heart rate algorithms in wearable device. Green light LED to direct heart rate is very popular in recent years which used analogy signal feedback to microcontroller calculation. Howev...
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ISBN:
(纸本)9781479985630
The paper proposed dynamic direct heart rate algorithms in wearable device. Green light LED to direct heart rate is very popular in recent years which used analogy signal feedback to microcontroller calculation. However, the different person physical signals are independent that including body fat, physical color, blood concentrations and oxygen concentration to influence observer data. Moreover, the body shock influence reflection feedback signal. This paper proposed automatic initial detect process and dynamic direct heart rate filter algorithms to process feedback analogy error noise. We presented a low cost solution for Texas Instruments AFE4403 heart rate oximeters with MSP430G2553 microcontroller to monitors body heart rate in wearable device. MSP430G2553 only have 512 byte RAM and 8k flash memory, so that the digital process calculation is an important topic. Finally, the experimental results show the dynamic algorithm has satisfactory performance.
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