This paper develops a new architecture for bearing fault diagnosis based on independent vector analysis, feature selection, and extreme learning machines classifiers. The suggested method applied to ...vibration signals includes the following steps: First, the independent vector analysis is introduced to separate vibration signal components from each other. Second, statistical parameters are extracted from all the obtained sources. Then three binary optimisation algorithms such as binary bat algorithm, binary particle swarm optimisation and binary grey wolf optimisation are employed for feature selection one by one. Finally, three classifiers based on extreme learning, artificial neural networks and random forest are used to perform the classification step. The obtained results show that independent vector analysis followed by feature selection based on binary grey wolf optimisation and classification using an extreme learning machine provides an optimal input vector which contains only five features for each sample and a very small misdiagnosis rate equal to 0.76%. The obtained results also prove that the suggested methodology gives the best classification results and high visibility compared to the other studied approaches.
Pregnancy may predispose to paroxysmal supraventricular tachycardia (SVT), in subjects with or without identifiable heart disease. Many physiological conditions such as autonomic nervous system ...changes, altered systemic hemodynamics, etc. can contribute to the onset of arrhythmias during pregnancy. Some cases reported the occurrence of arrhythmias in relation to systemic fluid variations. We report the case of a pregnant woman who experienced SVT due to fluid depletion, detected by bioimpedance vector analysis (BIVA), which was successfully treated by water repletion under tight BIVA monitoring. Emergency physicians can overcome dangerous drug administration by considering historical examination and using fast and reproducible techniques such as BIVA.
To establish a short rotation coppice (SRC) system in the temperate region of East Asia, planting was conducted for cuttings from seven species, including Salix eriocarpa, S. gilgiana, S. ...gracilistyla, S. integra, S. sachalinensis, S. serissaefolia, and S. subfragilis, with wide distribution in eastern Japan. During cultivation, cheap compost derived from swine manure and containing high concentrations of various nutrients was added. Three treatment groups, including control, low manure (5 Mg ha−1), and high manure (10 Mg ha−1) treatments, were established, and seven willows were grown for two complete growing seasons to obtain the clone density of 10,000 cuttings ha−1. The manure treatments accelerated the growth of all the willow species after two growing seasons. The averages of annual biomass production of seven willows grown under the control, low manure, and high manure treatments were 0.2 Mg ha−1yr−1, 5.3 Mg ha−1yr−1, and 8.5 Mg ha−1yr−1, respectively. By comparing with the biomasses of seven willows, the largest annual biomass production rates of 14.1 and 13.7 Mg ha−1yr−1 were observed in the high manure treatments of S. sachalinensis and S. subfragilis, respectively. For two species under the high manure treatment, S. sachalinensis had the thickest shoots, and S. subfragilis had the tallest shoots. These growth characteristics of S. sachalinensis and S. subfragilis originate from their high biomass production. Overall, these results suggest that S. sachalinensis and S. subfragilis are potentially feasible candidates for the SRC system in temperate regions of East Asia.
Based on updates to signal and image processing technology made in the last two decades, this text examines the most recent research results pertaining to Quaternion Fourier Transforms. QFT is a ...central component of processing color images and complex valued signals. The book's attention to mathematical concepts, imaging applications, and Matlab compatibility render it an irreplaceable resource for students, scientists, researchers, and engineers.
Soil salt content (SSC) is normally featured with obvious spatiotemporal variations in arid and semi-arid regions. Space factors such as elevation, temperature, and spatial locations are usually used ...as input variables for a model to estimate the SSC. However, whether temporal patterns of salt-affected soils (identified as temporal spectral patterns) can indicate the SSC level and be applied as a covariate in a model to estimate the SSC remains unclear. Hence, temporal changes in soil spectral patterns need to be characterized and explored as to their use as an input variable to improve SSC estimates. In this study, a total of 54 field samples and a time-series of Sentinel-2 multispectral images taken at monthly intervals (from October 2017 to April 2018) were collected in the Yinbei area of western China. Then, two-date satellite images were used to quantify significant spectral changes over time using spectral change vector analysis, and four two-date-based index methods were used to characterize soil spectral changes. Lastly, the optimal two-date-based spectral indices and multispectral bands were used as input variables to build the estimation models using a random forest algorithm. Results showed that the two-date-based spectral index could be applied as an input variable to improve the accuracy of SSC estimation at a regional scale. Temporal changes in salt-induced spectral patterns can be indicated by the band difference in the wavelength range from 400 nm to 900 nm. Three two-date-based indices designated as D28a (i.e., the band difference between band 2 from an image acquired in April 2018 and band 8a from an image acquired in December 2017), D22, and D28 were the optimal parameters for characterizing salt-induced spectral changes, which were dominated by the total brightness, chloride, and sulfate accumulation of the soils. The model did not yield satisfactory estimation results (RPD = 1.49) when multispectral bands were used as the input variables. Multispectral bands coupled with two two-date-based indices (D22 and D28a) used as the input variables produced the best estimation result (R2 = 0.92, RPD = 3.27). Incorporating multispectral bands and two-date-based indices into the random forest model provides a remotely-sensed strategy that effectively supports the monitoring of soil salt content.
Abstract
According to the data structure characteristics of educational resources, natural language processing technology is used to process the original educational resources data from the aspects ...of word segmentation processing, named entity recognition, part of speech tagging, synonym analysis, word vector analysis, etc. For complex image data, OCR preprocessing and coding format conversion are used to reduce the complexity of the original data; according to the difficulty requirements of the user to retrieve data, key words or ontology are selected to further expand and enrich the semantics and improve the accuracy of the retrieval results.
This paper focuses on the trajectory tracking control algorithm for Differential Wheeled Mobile Robots (DWMRs) based on rhombic input constraints. The kinematics and dynamics model of DWMRs are ...established, and vector analysis method is used to design the controller when the linear velocity and angular velocity of DWMRs were not mutually independently. Through the simulation of tracking 8-shaped curve, a good control performance is obtained.
Dynamics of the urban extent at fine spatial and temporal
resolutions over large areas are crucial for developing urban growth models
and achieving sustainable development goals. However, there are ...limited
practices of mapping urban dynamics with these two merits combined. In this
study, we proposed a new method to map urban dynamics from Landsat time
series data using the Google Earth Engine (GEE) platform and developed a
national dataset of annual urban extent (1985–2015) at a fine spatial
resolution (30 m) in the conterminous United States (US). First, we derived
the change information of urbanized years in four periods that were
determined from the National Land Cover Database (NLCD), using a temporal
segmentation approach. Then, we classified urban extents in the beginning (1985) and ending (2015) years at the cluster level through the implementation of a
change vector analysis (CVA)-based approach. We also developed a
hierarchical strategy to apply the CVA-based approach due to the spatially
explicit urban sprawl over large areas. The overall accuracy of mapped
urbanized years is around 90 % with the 1-year tolerance strategy. The
mapped urbanized areas in the beginning and ending years are reliable, with
overall accuracies of 96 % and 88 %, respectively. Our results reveal
that the total urban area increased by about 20 % during the period
of 1985–2015 in the US, and the annual urban area growth is not linear over the years. Overall, the growth pattern of urban extent in most coastal states is
plateaued over the past three decades while the states in the Midwestern US
show an accelerated growth pattern. The derived annual urban extents are of
great use for relevant urban studies such as urban area projection and urban
sprawl modeling over large areas. Moreover, the proposed mapping framework
is transferable for developing annual dynamics of urban extent in other
regions and even globally. The data are available at https://doi.org/10.6084/m9.figshare.8190920.v2 (Li et al.,
2019c).
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