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A Continuous Correlated Beta Process Model for Genetic Ancestry in Admixed Populations.
Published 2016-01-01“…In the current paper, I develop and test a continuous correlated beta process model to fill this analytical gap. …”
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Inference for the treatment effect in staircase designs with continuous outcomes: a simulation study
Published 2025-05-01“…We simulate staircase trial datasets with continuous outcomes and a repeated cross-sectional measurement scheme under exchangeable and block-exchangeable intracluster correlation structures, and then fit linear mixed models with linear and categorical time period effects. …”
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Generation of continuous variable quantum correlation via an optomechanical nanobeam crystal composed of dielectric material layers
Published 2025-04-01“…In this paper, we explore the generation of continuous-variable quantum correlations in an optomechanical nanobeam crystal, which consists of two dielectric mirrors designed as Bragg reflectors. …”
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The correlation between first-year outpatient follow-up frequency and outcome of patients with continuous ambulatory peritoneal dialysis
Published 2020-01-01“…Objective To investigate the correlation of clinical follow-up frequency with prognosis of patients with continuous ambulatory peritoneal dialysis(CAPD). …”
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Assessment of Correlation Between Glycaemic Variability Indices and Measures of Hypoglycaemia in Patients with Type 2 Diabetes Mellitus
Published 2024-11-01“…Methods: In this cross-sectional study, continuous glucose monitoring (CGM) was done for a period of 14 days in T2DM patients (n = 50). …”
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Dynamic Vision Sensor Tracking Method Based on Event Correlation Index
Published 2021-01-01“…This article proposes a method based on the event correlation index to obtain the object’s position, contour, and other information and is compatible with traditional tracking methods. …”
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Characteristics of Spot Spraying and Continuous Spraying Systems
Published 2025-05-01“…This paper studied the atomization characteristics of different spray nozzles under the spot spraying method and designed a test system for the atomization characteristics. …”
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Research on data-driven and correlation-based electric energy error analysis method
Published 2025-01-01“…On the basis of the continuous accumulation of operating errors in the power system, generate full-scale error data of the electric energy meter, divide the processed full-scale error time series and key features such as timeliness, identify the change points by comparing the Pearson correlation coefficient matrix of multiple acquisition periods, and establish a data-driven error correlation prediction model that does not depend on specific power consumption environments and only relies on the intrinsic components of the electric energy meter error. …”
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Separation of Body and Surface Wave Background Noise and Passive Seismic Interferometry Based on Synchrosqueezed Continuous Wavelet Transform
Published 2025-04-01“…In practical passive seismic data, body wave noise and surface wave noise often overlap in frequency bands, making it challenging to separate them effectively using conventional methods. The synchrosqueezed continuous wavelet transform, as a high-resolution time–frequency analysis method, can effectively capture the variations in frequency of passive seismic data. …”
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An improved neighbor-correlation-extended-Kalman-filter fusion method for indoor navigation
Published 2017-05-01“…In order to obtain high-accurate and continuous navigation information for indoor general devices in small computations, a novel combination of fusing extended Kalman filter and fingerprinting navigation algorithm, including K-nearest neighbor and Pearson correlation coefficient, is proposed in this article. …”
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Permanent terrestrial laser scanning for near-continuous environmental observations: Systems, methods, challenges and applications
Published 2025-08-01“…This paper provides an overview of different 4D systems for near-continuous laser scanning, and discusses systematic challenges including instability of the sensor system, meteorological and atmospheric influences, and data alignment, before discussing recently developed methods and scientific software for extracting and parameterizing changes from 4D topographic data sets, in connection to the different applications.…”
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Methods of Laser Spectroscopy in Devices for Continuous Monitoring of O2 and CO Content in Boiler Smoke Gases
Published 2006-02-01“…The paper shows that the least errors of continuous CO and O2 concentration monitoring at the presence of variations in dissipative losses have been ensured by the modified correlation method though its threshold sensitivity is less than integral and correlation ones.…”
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The Effect of Cone Area Variations on the Continuous Discharges Flow (CDF) Method Sedimentation Unit as a New Method for Raw Water Turbidity Removal
Published 2023-07-01“…The Sedimentation Unit Continuous Discharges Flow (CDF) method is a modification by adding a continuous and controlled discharge flow as a net force acting on the particles to increase the efficiency of turbidity removal by applying the principle of a leaky tank at the bottom of the settling zone. …”
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A Wi-Fi sensing method for complex continuous human activities based on CNN-BiGRU
Published 2023-12-01“…Human activity sensing based on Wi-Fi channel state information (CSI) has an important application prospect in future intelligent interaction scenarios such as virtual reality, intelligent games, and the metaverse.Accurate sensing of complex and continuous human activities is an important challenge for Wi-Fi sensing.Convolutional neural network (CNN) has the ability of spatial feature extraction but is poor at modeling the temporal features of the data.While long short-term memory (LSTM) network or gated recurrent unit (GRU) network, which are suitable for modeling time-series data, neglect learning spatial features of data.In order to solve this problem, an improved CNN that integrates bidirectional gated recurrent unit (BiGRU) network was proposed.The bi-directional feature extraction ability of BiGRU was used to capture the correlation and dependence of the front and back information in the time series data.The extraction of the spatiotemporal features of the time series CSI data was realized, and then the mapping relationship between the action and the CSI data was present.Thus the recognition accuracy of the complex continuous action was improved.The proposed network structure was tested with basketball actions.The results show that the recognition accuracy of this method is above 95% under various conditions.Compared with the traditional multi-layer perceptron (MLP), CNN, LSTM, GRU, and attention based bidirectional long short-term memory (ABLSTM) baseline methods, the recognition accuracy has been improved by 1%～20%.…”
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A Wi-Fi sensing method for complex continuous human activities based on CNN-BiGRU
Published 2023-12-01“…Human activity sensing based on Wi-Fi channel state information (CSI) has an important application prospect in future intelligent interaction scenarios such as virtual reality, intelligent games, and the metaverse.Accurate sensing of complex and continuous human activities is an important challenge for Wi-Fi sensing.Convolutional neural network (CNN) has the ability of spatial feature extraction but is poor at modeling the temporal features of the data.While long short-term memory (LSTM) network or gated recurrent unit (GRU) network, which are suitable for modeling time-series data, neglect learning spatial features of data.In order to solve this problem, an improved CNN that integrates bidirectional gated recurrent unit (BiGRU) network was proposed.The bi-directional feature extraction ability of BiGRU was used to capture the correlation and dependence of the front and back information in the time series data.The extraction of the spatiotemporal features of the time series CSI data was realized, and then the mapping relationship between the action and the CSI data was present.Thus the recognition accuracy of the complex continuous action was improved.The proposed network structure was tested with basketball actions.The results show that the recognition accuracy of this method is above 95% under various conditions.Compared with the traditional multi-layer perceptron (MLP), CNN, LSTM, GRU, and attention based bidirectional long short-term memory (ABLSTM) baseline methods, the recognition accuracy has been improved by 1%～20%.…”
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