A Proposal for an Open Source System of Development and Research for Music CAI

The purpose of this thesis is to examine the historical use of music Computer Assisted lnstruction (CAl) software to show that research on music CAl has decreased and to propose using a new method of coding and distribution (open source) that might increase research opportunities using music CAl. The reduction in research is due in part to limitations in existing software, as well as the practices of the music community. An open source CAl program called Mobius is described as an example of how open source programming can offer new opportunities for music researchers. CAl software has played a prominent role in the college music school, and has a long history of research and innovation. Early CAl was used in numerous studies to show how effective computers could be at delivering instruction, while reducing the teacher workload at the same time. As computers became more widely adopted, CAl became more commonplace in the music school, and many CAl software programmers sold their programs to fill the growing demand. Modern CAl is now viewed more as a commercial product, and less as a research tool. CAl can still be used as a powerful research tool. This thesis recommends using open source software development for music CAl since it allows programmers to share the workload of developing software, and allows CAl researchers to use existing open source as the basis for their new research programs. lncluded in this thesis are storyboards for several key components of an open source CAl program on music fundamentals, including an administrative portion, the actual CAl program, and a custom report builder

Bayesian-Augmented Identification of Stars in a Narrow View

An algorithm for the identification of stars from a charge-coupled-device (CCD) image of a star field has been extended for use with narrower field-of-view images. Previously, the algorithm had been shown to be effective at a field of view of 8 degrees. This work augments the earlier algorithm using Bayesian decision theory. The new algorithm is shown to be capable of effective star identification down to a field of view of 2 degrees. The algorithm was developed for use in estimating the attitude of a spacecraft and could be used on Earth to help in the identification of stars and other celestial objects for astronomical observations

Path Following with Slip Compensation for a Mars Rover

A software system for autonomous operation of a Mars rover is composed of several key algorithms that enable the rover to accurately follow a designated path, compensate for slippage of its wheels on terrain, and reach intended goals. The techniques implemented by the algorithms are visual odometry, full vehicle kinematics, a Kalman filter, and path following with slip compensation. The visual-odometry algorithm tracks distinctive scene features in stereo imagery to estimate rover motion between successively acquired stereo image pairs, by use of a maximum-likelihood motion-estimation algorithm. The full-vehicle kinematics algorithm estimates motion, with a no-slip assumption, from measured wheel rates, steering angles, and angles of rockers and bogies in the rover suspension system. The Kalman filter merges data from an inertial measurement unit (IMU) and the visual-odometry algorithm. The merged estimate is then compared to the kinematic estimate to determine whether and how much slippage has occurred. The kinematic estimate is used to complement the Kalman-filter estimate if no statistically significant slippage has occurred. If slippage has occurred, then a slip vector is calculated by subtracting the current Kalman filter estimate from the kinematic estimate. This slip vector is then used, in conjunction with the inverse kinematics, to determine the wheel velocities and steering angles needed to compensate for slip and follow the desired path

Projection of Stabilized Aerial Imagery Onto Digital Elevation Maps for Geo-Rectified and Jitter-Free Viewing

As imagery is collected from an airborne platform, an individual viewing the images wants to know from where on the Earth the images were collected. To do this, some information about the camera needs to be known, such as its position and orientation relative to the Earth. This can be provided by common inertial navigation systems (INS). Once the location of the camera is known, it is useful to project an image onto some representation of the Earth. Due to the non-smooth terrain of the Earth (mountains, valleys, etc.), this projection is highly non-linear. Thus, to ensure accurate projection, one needs to project onto a digital elevation map (DEM). This allows one to view the images overlaid onto a representation of the Earth. A code has been developed that takes an image, a model of the camera used to acquire that image, the pose of the camera during acquisition (as provided by an INS), and a DEM, and outputs an image that has been geo-rectified. The world coordinate of the bounds of the image are provided for viewing purposes. The code finds a mapping from points on the ground (DEM) to pixels in the image. By performing this process for all points on the ground, one can "paint" the ground with the image, effectively performing a projection of the image onto the ground. In order to make this process efficient, a method was developed for finding a region of interest (ROI) on the ground to where the image will project. This code is useful in any scenario involving an aerial imaging platform that moves and rotates over time. Many other applications are possible in processing aerial and satellite imagery

Automated Camera Array Fine Calibration

Using aerial imagery, the JPL FineCalibration (JPL FineCal) software automatically tunes a set of existing CAHVOR camera models for an array of cameras. The software finds matching features in the overlap region between images from adjacent cameras, and uses these features to refine the camera models. It is not necessary to take special imagery of a known target and no surveying is required. JPL FineCal was developed for use with an aerial, persistent surveillance platform

Forty-two counterparts for Vladislav Blazhevich "70 Studies for BBb Tuba Vol. I"

The purpose of this project was to write duet counterparts for Vladislav Blazhevich's etude book, 70 Studies for BBb Tuba and to establish a desire for these duets among college applied-tuba teachers. A short biography of Blazhevich and history of his works is provided. A review of tuba pedagogy literature found little information regarding what materials are standard in studio teaching. Following this review, a survey was sent to 120 college teachers of tuba to determine what etudes are most often used, and how frequently 70 Studies for BBb Tuba is used in studio teaching. The survey was also used to determine how frequently and what duet materials were used in college teaching. Finally, it was determined in the results of the survey whether the tuba-teaching community might use duet counterparts for 70 Studies for BBb Tuba. The results were used to establish that a majority of tuba teachers use 70 Studies for BBb Tuba, and a majority use duet materials in their teaching. It was also determined that of those surveyed, there is a desire for duet counterparts for 70 Studies for BBb Tuba. A set of 42 duet counterparts was written to accompany the first volume of 70 Studies for BBb Tuba by Blazhevich. The counterparts were written mindful of the advice and requests gleaned in the survey. Finally, two areas for further study were proposed. First, there are few available accounts of Blazhevich's life and works, though his music is often played. There is opportunity for more scholarly work on his life and works. Second, 70 Studies for BBb Tuba is a two-volume set. Counterparts can be written to accompany the second volume

Phylotranscriptomic analysis uncovers a wealth of tissue inhibitor of metalloproteinases variants in echinoderms

Tissue inhibitors of metalloproteinases (TIMPs) help regulate the extracellular matrix (ECM) in animals, mostly by inhibiting matrix metalloproteinases (MMPs). They are important activators of mutable collagenous tissue (MCT), which have been extensively studied in echinoderms, and the four TIMP copies in humans have been studied for their role in cancer. To understand the evolution of TIMPs, we combined 405 TIMPs from an echinoderm transcriptome dataset built from 41 specimens representing all five classes of echinoderms with variants from protostomes and chordates. We used multiple sequence alignment with various stringencies of alignment quality to cull highly divergent sequences and then conducted phylogenetic analyses using both nucleotide and amino acid sequences. Phylogenetic hypotheses consistently recovered TIMPs as diversifying in the ancestral deuterostome and these early lineages continuing to diversify in echinoderms. The four vertebrate TIMPs diversified from a single copy in the ancestral chordate, all other copies being lost. Consistent with greater MCT needs owing to body wall liquefaction, evisceration, autotomy and reproduction by fission, holothuroids had significantly more TIMPs and higher read depths per contig. Ten cysteine residues, an HPQ binding site and several other residues were conserved in at least 70% of all TIMPs. The conservation of binding sites and the placement of echinoderm TIMPs involved in MCT modification suggest that ECM regulation remains the primary function of TIMP genes, although within this role there are a large number of specialized copies

Constructing a Database from Multiple 2D Images for Camera Pose Estimation and Robot Localization

The LMDB (Landmark Database) Builder software identifies persistent image features (landmarks) in a scene viewed multiple times and precisely estimates the landmarks 3D world positions. The software receives as input multiple 2D images of approximately the same scene, along with an initial guess of the camera poses for each image, and a table of features matched pair-wise in each frame. LMDB Builder aggregates landmarks across an arbitrarily large collection of frames with matched features. Range data from stereo vision processing can also be passed to improve the initial guess of the 3D point estimates. The LMDB Builder aggregates feature lists across all frames, manages the process to promote selected features to landmarks, and iteratively calculates the 3D landmark positions using the current camera pose estimations (via an optimal ray projection method), and then improves the camera pose estimates using the 3D landmark positions. Finally, it extracts image patches for each landmark from auto-selected key frames and constructs the landmark database. The landmark database can then be used to estimate future camera poses (and therefore localize a robotic vehicle that may be carrying the cameras) by matching current imagery to landmark database image patches and using the known 3D landmark positions to estimate the current pose

Real-Time Feature Tracking Using Homography

This software finds feature point correspondences in sequences of images. It is designed for feature matching in aerial imagery. Feature matching is a fundamental step in a number of important image processing operations: calibrating the cameras in a camera array, stabilizing images in aerial movies, geo-registration of images, and generating high-fidelity surface maps from aerial movies. The method uses a Shi-Tomasi corner detector and normalized cross-correlation. This process is likely to result in the production of some mismatches. The feature set is cleaned up using the assumption that there is a large planar patch visible in both images. At high altitude, this assumption is often reasonable. A mathematical transformation, called an homography, is developed that allows us to predict the position in image 2 of any point on the plane in image 1. Any feature pair that is inconsistent with the homography is thrown out. The output of the process is a set of feature pairs, and the homography. The algorithms in this innovation are well known, but the new implementation improves the process in several ways. It runs in real-time at 2 Hz on 64-megapixel imagery. The new Shi-Tomasi corner detector tries to produce the requested number of features by automatically adjusting the minimum distance between found features. The homography-finding code now uses an implementation of the RANSAC algorithm that adjusts the number of iterations automatically to achieve a pre-set probability of missing a set of inliers. The new interface allows the caller to pass in a set of predetermined points in one of the images. This allows the ability to track the same set of points through multiple frames