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Student performance depends not only on their intellectual ability, but also their habits and decision making. Homework assignments can directly affect student performance in a course, but also indirectly through preparation for exams.... more
Student performance depends not only on their intellectual ability, but also their habits and decision making. Homework assignments can directly affect student performance in a course, but also indirectly through preparation for exams. This is specifically prevalent for engineering courses which involve homework assignments as practice problem sets to prepare for examination questions. This work investigates the differences in grade performance between two student groups within an engineering dynamics course: those who voluntarily picked up a graded homework assignment prior to an exam, and those who did not. Results from this research effort indicate that on average students who picked up their assignment performed better on the assignment, the midterm exam, and the overall course grade, however statistical significance was only found for the final course grade.
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Autonomous formation flight is a key approach for reducing energy cost and managing traffic in future high density airspace. The use of Unmanned Aerial Vehicles (UAVs) has allowed low-budget and low-risk validation of autonomous formation... more
Autonomous formation flight is a key approach for reducing energy cost and managing traffic in future high density airspace. The use of Unmanned Aerial Vehicles (UAVs) has allowed low-budget and low-risk validation of autonomous formation flight concepts. This paper discusses the implementation and flight testing of nonlinear dynamic inversion (NLDI) controllers for close formation flight (CFF) using two distinct UAV platforms: a set of fixed wing aircraft named “Phastball” and a set of quadrotors named “NEO.” Experimental results show that autonomous CFF with approximately 5-wingspan separation is achievable with a pair of low-cost unmanned Phastball research aircraft. Simulations of the quadrotor flight also validate the design of the NLDI controller for the NEO quadrotors.
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Engineering laboratory courses often contain laboratory reports as writing assignments to be used as an assessment and grading tool for the course. While laboratory report writing is a useful skill, this article discusses an assignment... more
Engineering laboratory courses often contain laboratory reports as writing assignments to be used as an assessment and grading tool for the course. While laboratory report writing is a useful skill, this article discusses an assignment which was used as an alternative to a traditional laboratory report within a dynamic systems laboratory course. This writing assignment is framed within the context of a hypothetical scenario involving a supervisor requesting a laboratory experiment to compare the effectiveness of two different designs for controlling the speed of a gearbox unit. Performance goals are specified by the ``customer'' so that students have a reference with which to frame their responses. Despite the shortened length of the writing assignment, students are forced to apply critical thinking and use evidence from their experiments to answer the posed question with a clear conclusion.
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QUESTION: How accurate are the step counts obtained from Apple Watch? In this validation study, video steps vs. Apple Watch steps (mean ± SD) were 2965 ± 144 vs. 2964 ± 145 steps; P < 0.001. Lin's concordance correlation... more
QUESTION: How accurate are the step counts obtained from Apple Watch? In this validation study, video steps vs. Apple Watch steps (mean ± SD) were 2965 ± 144 vs. 2964 ± 145 steps; P < 0.001. Lin's concordance correlation coefficient showed a strong correlation (r = 0.96; P < 0.001) between the two measurements. There was a total error of 0.034% (1.07 steps) for the Apple Watch steps when compared with the manual counts obtained from video recordings. Our study is one of the initial studies to objectively validate the accuracy of the step counts obtained from Apple watch at different walking speeds. Apple Watch tested to be an extremely accurate device for measuring daily step counts for adults.
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Objectives: Central obesity is a greater risk factor for cardiovascular disease (CVD) compared to other types of obesity. The purpose of our study was to assess cardiometabolic risk factors using various anthropometric measurements such... more
Objectives: Central obesity is a greater risk factor for cardiovascular disease (CVD) compared to other types of obesity. The purpose of our study was to assess cardiometabolic risk factors using various anthropometric measurements such as waist circumference (WC), hip circumference (HC), waist-to-hip-circumference (WHR), total body fat; measure blood pressure (BP) and evaluate sedentary behavior among University students in the USA. Methods: Sixty, apparently healthy students (29 M/31F; 21.5 ± 2.8yrs) were recruited. Height and weight were measured using a Health-O-Meter Stadiometer and body mass index (BMI) was calculated. Automated BP measurements were obtained using the Welch Allyn Connex-ProBP digital device. Fitbit Charge-HR activity monitor was deployed for a week to assess sedentary activity. Omron HBF-516F bioimpedance device was used to assess total body fat. Horizontal measures obtained at the height of the iliac crest and the maximal circumference of buttocks were defined as waist circumference and hip circumference, respectively. Results: Normotensives (N = 31; 109.9 ± 65.4mmHg) vs. Prehypertensives (N = 29; 128.1 ± 70.5mmHg) BMI (23.3 ± 3.5 vs. 28.2 ± 5.5 kg/m2), WC (72.0 ± 6.9 vs. 85.7 ± 9.6 cm; p < 0.001), HC (93.9 ± 8.7 vs. 103.0 ± 13.1 cm; p = 0.004), WHR (0.77 ± 0.06 vs. 0.84 ± 0.07; p < 0.001) were statistically significant. Sedentary time/wk (4473.1 ± 1207 vs. 4401.9 ± 1265 min; p > 0.05) and total body fat (29.2 ± 9.0 vs. 29.9 ± 12.9%; p > 0.05) were not significant. Conclusion: Prehypertensives were overweight and have high WC, HC and WHR compared to normotensives with the similar sedentary time and total body fat. The additional measure of WC among overweight students seems to be relevant in identifying those at increased risk of high BP. This highlights the importance of weight management in the prevention of CVD in this population.
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A novel sensor fusion design framework is presented with the objective of improving the overall multisensor measurement system performance and achieving graceful degradation following individual sensor failures. The Unscented Information... more
A novel sensor fusion design framework is presented with the objective of improving the overall multisensor measurement system performance and achieving graceful degradation following individual sensor failures. The Unscented Information Filter (UIF) is used to provide a useful tool for combining information from multiple sources. A two-step off-line and on-line calibration procedure refines sensor error models and improves the measurement performance. A Fault Detection and Identification (FDI) scheme crosschecks sensor measurements and simultaneously monitors sensor biases. Low-quality or faulty sensor readings are then rejected from the final sensor fusion process. The attitude estimation problem is used as a case study for the multiple sensor fusion algorithm design, with information provided by a set of low-cost rate gyroscopes, accelerometers, magnetometers, and a single-frequency GPS receiver’s position and velocity solution. Flight data collected with an Unmanned Aerial Vehic...
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This paper offers a set of novel navigation techniques that rely on the use of inertial sensors and wide-field optical flow information. The aircraft ground velocity and attitude states are estimated with an Unscented Information Filter... more
This paper offers a set of novel navigation techniques that rely on the use of inertial sensors and wide-field optical flow information. The aircraft ground velocity and attitude states are estimated with an Unscented Information Filter (UIF) and are evaluated with respect to two sets of experimental flight data collected from an Unmanned Aerial Vehicle (UAV). Two different formulations are proposed, a full state formulation including velocity and attitude and a simplified formulation which assumes that the lateral and vertical velocity of the aircraft are negligible. An additional state is also considered within each formulation to recover the image distance which can be measured using a laser rangefinder. The results demonstrate that the full state formulation is able to estimate the aircraft ground velocity to within 1.3 m/s of a GPS receiver solution used as reference “truth” and regulate attitude angles within 1.4 degrees standard deviation of error for both sets of flight data.
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A measurement device that is extremely important for Unmanned Aerial Vehicle (UAV) guidance and control purposes is the airspeed sensor. As the parameters of feedback control laws are conventionally scheduled as a function of airspeed, an... more
A measurement device that is extremely important for Unmanned Aerial Vehicle (UAV) guidance and control purposes is the airspeed sensor. As the parameters of feedback control laws are conventionally scheduled as a function of airspeed, an incorrect reading (e.g. due to a sensor fault) of the Pitot-static tube could induce an incorrect feedback control action, potentially leading to the loss of control of the UAV. The objective of this study is to establish the accuracy and reliability of the two airspeed estimation techniques for eventual use as the basis for real-time fault detection of anomalies occurring on the Pitot-static tube sensor. The first approach is based on an Extended Kalman Filter (EKF) and the second approach is based on Least Squares (LS) modeling. The EKF technique utilizes nonlinear kinematic relations between GPS, Inertial Measurement Unit and Air Data System signals and has the advantage of independence from knowledge of the aircraft model. The LS method is based on explicit knowledge of the aircraft model and has the advantage of on-line computation of the airspeed estimate, with minimal computational effort. The performance analysis was carried out with flight data from the WVU YF-22 UAV research platform. The results of the analysis indicate that the two methods provide essentially comparable performance in terms of mean ( 3c1 m/s) and standard deviation ( 3c1.5 m/s) of the airspeed estimation error which is about the 5% of the mean in-flight velocity of 32 m/s
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Due to civilian noise complaints and damage claims, there is a need to establish an accurate record of impulse noise generated at military installations. Current noise monitoring systems are susceptible to false positive detection of... more
Due to civilian noise complaints and damage claims, there is a need to establish an accurate record of impulse noise generated at military installations. Current noise monitoring systems are susceptible to false positive detection of impulse events due to wind noise. In order to analyze the characteristics of noise events, multiple channel data methods were investigated. A microphone array was used to collect four channel data of military impulse noise and wind noise. These data were then analyzed using cross-correlation functions to characterize the input waveforms. Four different analyses of microphone array data are presented. A new value, the min peak correlation coefficient, is defined as a measure of the likelihood that a given waveform originated from a correlated noise source. Using a sound source localization technique, the angle of incidence of the noise source can be calculated. A method was also developed to combine the four individual microphone channels into one. This ...
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Impulse noise monitoring systems are needed for quantifying the magnitude and time of impulsive noise events to ensure compliance and to provide an archival record of noise emanating from military installations. Currently, there are... more
Impulse noise monitoring systems are needed for quantifying the magnitude and time of impulsive noise events to ensure compliance and to provide an archival record of noise emanating from military installations. Currently, there are several commercial systems; however, they report an overwhelming number of false events generated by windborne noise and distant non-military acoustic events. This can bias noise statistics to the point where a meaningful assessment of the acoustic sound levels from a site is not possible. APS, in collaboration with the University of Pittsburgh, have developed an improved noise monitoring system for mitigating windborne and other sources of non-military noise. This system includes a collection of remote sensors capable of detection, localization, and classification. Each sensor uses an acoustic array and real-time signal processing codes to estimate the noise source location. Mitigation of windborne events is accomplished using cross-channel correlation ...
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Research Interests: Computer Science, Seismic data processing, Kalman Filter, Database Management Systems and Querry Processing, Data Mining in Image Processing, and 15 moreKalman Filtering, Data Acquisition and Signal Processing, Tutorial, Large Scale Data Processing, Acquisition and Processing of Seismic Reflection Data, Kalman Filtering & Unscented Filtering, Real-Time Data Processing, MODIS data processing for global environment monitoring, Data Processing, Filtering, Big Data Graph Processing, Kalman Filtering Algorithm, Kalman Filtering and Estimation, Automated Data Delivery and Processing for Disaster Events, and Kalman filtering and smoothing
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ABSTRACT Close Formation Flight is a key potential approach for reducing greenhouse gas emissions and managing traffic in future high density airspace. This paper discusses the implementation and flight testing of a formation flight... more
ABSTRACT Close Formation Flight is a key potential approach for reducing greenhouse gas emissions and managing traffic in future high density airspace. This paper discusses the implementation and flight testing of a formation flight controller. Experimental results show that an autonomous close formation flight with approximately 5-wingspan separation is achievable with a pair of low-cost unmanned research aircraft.
ABSTRACT This document presents a sensitivity analysis relative to different algorithm design parameters on the attitude performance of two different Global Positioning System/Inertial Navigation System (GPS/INS) sensor fusion algorithms... more
ABSTRACT This document presents a sensitivity analysis relative to different algorithm design parameters on the attitude performance of two different Global Positioning System/Inertial Navigation System (GPS/INS) sensor fusion algorithms for estimating aircraft attitude angles, namely the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF). The sensor fusion was performed using flight data acquired with three different WVU YF-22 research aircraft under a variety of flight conditions. The attitude estimates were compared with direct ‘truth’ measurements from an on-board mechanical vertical gyroscope. The sensitivity analysis was conducted on the following parameters: process and measurement noise covariance tuning, IMU and GPS sampling rates, GPS outages, time offset between GPS and IMU measurements, and acceleration due to gravity. Overall, the EKF and UKF performed very similarly in response to the different parameters for this study.
ABSTRACT This paper presents the development of a GPS/INS sensor fusion simulation environment through the use of WVU YF-22 flight data. Noise on the GPS measurements was modeled using satellite ephemeral data as well as recorded flight... more
ABSTRACT This paper presents the development of a GPS/INS sensor fusion simulation environment through the use of WVU YF-22 flight data. Noise on the GPS measurements was modeled using satellite ephemeral data as well as recorded flight data. The noise characteristics of the IMU were determined from an Allan variance approach. The GPS and IMU noise models were implemented in the WVU formation flight simulator, which includes an EKF-based sensor fusion algorithm to estimate the position, velocity, and attitude of the aircraft. Using both simulated and recorded flight data, attitude estimation results were used to evaluate the accuracy of the GPS and IMU measurement noise models, since the flight data includes a high quality measurement of the roll and pitch angles from a mechanical vertical gyroscope. It was determined from this analysis that the simulator includes a realistic model of the noise present in recorded flight data, which allows for validation and analysis of sensor fusion algorithms.
ABSTRACT In this paper, calibration modeling of a low-cost Inertial Measurement Unit (IMU) sensor for Small Unmanned Aerial Vehicle (SUAV) attitude estimation is considered. First, an Allan variance analysis method is used to determine... more
ABSTRACT In this paper, calibration modeling of a low-cost Inertial Measurement Unit (IMU) sensor for Small Unmanned Aerial Vehicle (SUAV) attitude estimation is considered. First, an Allan variance analysis method is used to determine stochastic noise model parameters for each sensor of a Micro-Electro-Mechanical-System (MEMS) IMU. Next, these models are included in a Global Positioning System/Inertial Navigation System (GPS/INS) sensor fusion algorithm for on-line calibration. In addition, an off-line magnetometer calibration is considered that uses a set of GPS/INS sensor fusion attitude estimates to derive a calibration model. This off-line magnetometer calibration model is then augmented on-line with sensor fusion estimates of the residual sensor biases. Finally, using the calibrated magnetometers, attitude estimation is considered that uses only a low-cost IMU with magnetometers. Each sensor fusion algorithm is formulated using an Unscented Kalman Filter (UKF). For performance validation, attitude estimates are calculated with data collected on-board a SUAV and are compared with high-quality vertical gyroscope measurements.
ABSTRACT Traditional approaches to sensor fault tolerance for flight control systems have been based on triple or quadruple physical redundancy. However, recent events have highlighted the criticality of “common mode” failures on the Air... more
ABSTRACT Traditional approaches to sensor fault tolerance for flight control systems have been based on triple or quadruple physical redundancy. However, recent events have highlighted the criticality of “common mode” failures on the Air Data System (ADS). In fact, since the parameters of flight control laws are typically scheduled as a function of airspeed, incorrect readings from the ADS can lead to potentially catastrophic conditions. In this paper, we describe the evaluation of an analytical redundancy-based approach to the problem of Sensor Failure Accommodation following simulated failures on the ADS of a research UAV, using Artificial Neural Networks (ANNs). Specifically, two different neural networks are evaluated - the Extended Minimal Resource Allocating Network and a Multilayer Feedforward NN. These neural networks are trained and validated using experimental flight data from the WVU YF-22 research aircraft which was designed, manufactured, instrumented, and flight tested by researchers at the Flight Control Systems Laboratory at West Virginia University. The performance of the two approaches is evaluated in terms of the statistics of the tracking error in the estimation of the airspeed, as compared to actual measurements from the ADS, operating under nominal conditions.
ABSTRACT Wind and turbulence, including wakes induced by leading aircraft, have a large impact on flight performance and flight safety of both manned and unmanned aircraft. An accurate real-time wind estimation technique is crucial for... more
ABSTRACT Wind and turbulence, including wakes induced by leading aircraft, have a large impact on flight performance and flight safety of both manned and unmanned aircraft. An accurate real-time wind estimation technique is crucial for tasks such as increasing air traffic capacity, commercial formation flight, or aerial refueling, etc. A leader-follower formation flight of Phastball Unmanned Aerial Vehicles (UAVs) were used as the experimental platform for the above problem. The air data system of Phastball UAV was developed with pitot-tube and flow-angle sensors. Using the designed system, two Unscented Kalman Filters (one standalone UKF and one cooperative UKF) were developed for the wind field estimation with and without using the wake information from the leader aircraft. For close formation flights, the wake of the leader is assumed to be predictable by certain wake models for the follower aircraft. Flight data showed the effectiveness of the standalone EKF for the wind estimation compared with the ground weather station measurements. Simulation results showed the advantage of the cooperative UKF over the standalone UKF.