A Novel Separated Position and Orientation System Integrated with Inertially Stabilized Platform

Considering the application requirements of independent imaging payloads design, a novel scheme of separated position and orientation system (POS) is proposed, in which the high-precision inertial sensors of traditional centralized POS fixed on the imaging payloads are mounted on three gimbals of the inertially stabilized platform (ISP), respectively, and make them integrated. Then, the kinematics model of the ISP system is built to transmit the inertial information measured by separated inertial sensors mounted on ISP gimbals and flight body to the imaging payloads, calculating the position and attitude of the imaging payloads to achieve the function of separated POS. Based on the model, a series of simulations indicate that the precision difference between separated system and centralized system is ignorable under the condition of angular motion and variable velocity motion. Besides the effective function equal to traditional centralized system, the separated POS enhances the integration with the ISP. Moreover, it improves the design independence of the imaging payloads significantly

Diagnostic value of circulating miR-155 for breast cancer: a meta-analysis

BackgroundsThe value of circulating microRNA (miR)-155 for breast cancer (BC) diagnosis may differ in different studies. Therefore, we conducted this systematic review and meta-analysis to evaluate the potential application of circulating miR-155 in the diagnosis of BC.MethodsArticles published before December 2023 and in English were searched in these databases: PubMed, Web of Science, Medline, EMBASE and Google Scholar. A summary of sensitivity, specificity, positive likelihood ratios (PLR), negative likelihood ratios (NLR), and diagnostic odds ratio (DOR) were calculated from the true positive (TP), true negative (TN), false positive (FP) and false negative (FN) of each study. Additionally, the summary receive-operating characteristics (SROC) curve was constructed to summarize the TP and FP rates.ResultsThe pooled parameters calculated were as follows: sensitivity, 0.93 (95% CI: 0.83-0.97); specificity, 0.85 (95% CI: 0.74-0.92); PLR, 6.4 (95% CI: 3.4-11.9); NLR, 0.09 (95% CI: 0.04-0.20); and DOR, 74 (95% CI: 22-247). The analysis showed a significant heterogeneity (sensitivity, I2 = 95.19%, p < 0.001; specificity, I2 = 95.29%, p < 0.001; DOR, I2 = 92.9%, p < 0.001). The SROC curve was with an area under curve (AUC) of 0.95 (95% CI: 0.93-0.97).ConclusionCirculating miR-155 has a potential in the diagnosis of BC

A New Open-Loop Fiber Optic Gyro Error Compensation Method Based on Angular Velocity Error Modeling

With the open-loop fiber optic gyro (OFOG) model, output voltage and angular velocity can effectively compensate OFOG errors. However, the model cannot reflect the characteristics of OFOG errors well when it comes to pretty large dynamic angular velocities. This paper puts forward a modeling scheme with OFOG output voltage and temperature as the input variables and angular velocity error as the output variable. Firstly, the angular velocity error is extracted from OFOG output signals, and then the output voltage , temperature and angular velocity error are used as the learning samples to train a Radial-Basis-Function (RBF) neural network model. Then the nonlinear mapping model over T, and is established and thus can be calculated automatically to compensate OFOG errors according to and . The results of the experiments show that the established model can be used to compensate the nonlinear OFOG errors. The maximum, the minimum and the mean square error of OFOG angular velocity are decreased by , and relative to their initial values, respectively. Compared with the direct modeling of gyro angular velocity, which we researched before, the experimental results of the compensating method proposed in this paper are further reduced by , and , respectively, so the performance of this method is better than that of the direct modeling for gyro angular velocity

A PEDESTRIAN STEP COUNTING PARAMETER DETECTION METHOD AIDED WITH ANGULAR VELOCITY INFORMAITON

In waist-worn pedestrian navigation systems, the peak detection method accuracy will be reduced when pedestrian carries on activities ups and downs in-situ such as stooped to and fro,squatting up and down. To compensate this error,a pedestrian step detection method aided with angular velocity is proposed based on the analysis on body waist motion feature. This method first extracts body’s forward angular velocity and lateral one to judge whether pedestrian walks ahead. Then peak signal of vertical accelerometer output is used to detect steps in common. In 27 experiments,which pedestrian walked certain steps and interference of activities ups and downs in-situ were brought in,the average accuracy rate of peak detection method and this method was 85. 8%,98. 84% respectively. Experimental results demonstrate that the proposed method can effectively reduce step detection errors generated by walking ups and downs in-situ with a high reliability

A New Open-Loop Fiber Optic Gyro Error Compensation Method Based on Angular Velocity Error Modeling

With the open-loop fiber optic gyro (OFOG) model, output voltage and angular velocity can effectively compensate OFOG errors. However, the model cannot reflect the characteristics of OFOG errors well when it comes to pretty large dynamic angular velocities. This paper puts forward a modeling scheme with OFOG output voltage  and temperature  as the input variables and angular velocity error  as the output variable. Firstly, the angular velocity error  is extracted from OFOG output signals, and then the output voltage , temperature  and angular velocity error  are used as the learning samples to train a Radial-Basis-Function (RBF) neural network model. Then the nonlinear mapping model over T,  and  is established and thus  can be calculated automatically to compensate OFOG errors according to  and . The results of the experiments show that the established model can be used to compensate the nonlinear OFOG errors. The maximum, the minimum and the mean square error of OFOG angular velocity are decreased by ,  and  relative to their initial values, respectively. Compared with the direct modeling of gyro angular velocity, which we researched before, the experimental results of the compensating method proposed in this paper are further reduced by ,  and , respectively, so the performance of this method is better than that of the direct modeling for gyro angular velocity

An Adaptive Filtering Approach Based on the Dynamic Variance Model for Reducing MEMS Gyroscope Random Error

To improve the dynamic random error compensation accuracy of the Micro Electro Mechanical System (MEMS) gyroscope at different angular rates, an adaptive filtering approach based on the dynamic variance model was proposed. In this paper, experimental data were utilized to fit the dynamic variance model which describes the nonlinear mapping relations between the MEMS gyroscope output data variance and the input angular rate. After that, the dynamic variance model was applied to online adjustment of the Kalman Filter measurement noise coefficients. The proposed approach suppressed the interference from the angular rate in the filtering results. Dynamic random errors were better estimated and reduced. Turntable experiment results indicated that the adaptive filtering approach compensated for the MEMS gyroscope dynamic random error effectively both in the constant angular rate condition and the continuous changing angular rate condition, thus achieving adaptive dynamic random error compensation

The Height-Adaptive Parameterized Step Length Measurement Method and Experiment Based on Motion Parameters

In order to tackle the inaccurate step length measurement of people with different heights and in different motion states, a height-adaptive method of step length measurement based on motion parameters is proposed in this paper. This method takes people’s height, stride frequency, and changing accelerometer output while walking into integrated consideration, and builds a dynamic and parameterized model of their step length. In this study, these parameters were calibrated with thirty sets of experiment data from people with different heights and in different motion states, which were then verified experimentally by motion data of randomly selected subjects, regardless of speed and height. The experiment results indicate that the height-adaptive step length measurement was realized, thus eliminating the influence of height exerted on step length measurement