Creating the Carrot

O’Leary, Ronald, M.A., Summer 2010: Integrated Arts and Education Introducing Media Arts as a Motivational and Educational Tool Chairperson: Richard Hughes Drawing from a wide swath of fine arts disciplines, this project effectively deals with pulling music, movement, creative writing, video and collaborative learning experiences together. Leading other teachers in the direction of media arts is the additional goal, which continues to be a monumental challenge in the face of working with very difficult students at the Yellowstone Academy. The Yellowstone Academy is a K-12 school, which serves the Yellowstone Boys and Girl’s Ranch (a treatment center for emotionally disturbed youth). Creating sound tracks and video projects has proven to be an effective motivator for many of the students in my music classes. Students engage in the subject matter, think creatively and produce culturally relevant artistic projects. Reaching out to the other teachers has run parallel to my own pursuits, as I see so many possibilities for affecting change through media arts. My pursuit of bringing media arts to the Yellowstone Academy has become a reality, in spite of the odds. The overall involvement and growth of individual students and the overall tone and culture of my music classes as a media arts component develops will be addressed within the scope of this paper. This project culminates many facets of the arts and brings my own development as an educator and artist into the technological realm. My greatest ambition is that over time, the motivational quality of integrating video technology to other areas of the Yellowstone Academy will create a positive influence on the culture of the student body

Orbital Flight Preparations of Get Away Special Payload G-572: Design and Testing of Electrical Systems

Orbital measurements of the cardiac function of Space Shuttle crew members have shown an initial increase in cardiac stroke volume upon entry into weightlessness followed by a gradual reduction in stroke volume. In an effort to explain this response, it was postulated that gravity plays a role in cardiac filling. A mock circulation system was designed to investigate this effect. Preliminary studies carried out on the NASA KC-135 aircraft, which provides brief periods of weightlessness, showed a strong correlation between cardiac filling, stroke volume, and the presence or absence of gravity. The need for extended periods of high quality zero gravity was identified to verify this observation. To accomplish this, the aircraft version of the experiment was reduced in size and fully automated for eventual integration into a Get-Away-Special canister for the orbital version of the experiment. Three nonlinearities, that govern the ability of the apparatus to regulate to a mean cardiac outflow pressure of 95 mm Hg, were identified and minimized. In preparation for an anticipated 1997 shuttle flight, the automated system was again flown aboard the KC-135. The control algorithm was successful in carrying out the experimental protocol, including regulation of mean outflow pressure

A sinusoidal signal reconstruction method for the inversion of the mel-spectrogram

The synthesis of sound via deep learning methods has recently received much attention. Some problems for deep learning approaches to sound synthesis relate to the amount of data needed to specify an audio signal and the necessity of preserving both the long and short time coherence of the synthesised signal. Visual time-frequency representations such as the log-mel-spectrogram have gained in popularity. The log- mel-spectrogram is a perceptually informed representation of audio that greatly compresses the amount of information required for the description of the sound. However, because of this compression, this representation is not directly invertible. Both signal processing and machine learning techniques have previ- ously been applied to the inversion of the log-mel-spectrogram but they both caused audible distortions in the synthesised sounds due to issues of temporal and spectral coherence. In this paper, we outline the application of a sinusoidal model to the ‘inversion’ of the log-mel-spectrogram for pitched musical instrument sounds outperforming state-of-the-art deep learning methods. The approach could be later used as a general decoding step from spectral to time intervals in neural applications

Audio representations for deep learning in sound synthesis: A review

The rise of deep learning algorithms has led many researchers to withdraw from using classic signal processing methods for sound generation. Deep learning models have achieved expressive voice synthesis, realistic sound textures, and musical notes from virtual instruments. However, the most suitable deep learning architecture is still under investigation. The choice of architecture is tightly coupled to the audio representations. A sound’s original waveform can be too dense and rich for deep learning models to deal with efficiently - and complexity increases training time and computational cost. Also, it does not represent sound in the manner in which it is perceived. Therefore, in many cases, the raw audio has been transformed into a compressed and more meaningful form using upsampling, feature-extraction, or even by adopting a higher level illustration of the waveform. Furthermore, conditional on the form chosen, additional conditioning representations, different model architectures, and numerous metrics for evaluating the reconstructed sound have been investigated. This paper provides an overview of audio representations applied to sound synthesis using deep learning. Additionally, it presents the most significant methods for developing and evaluating a sound synthesis architecture using deep learning models, always depending on the audio representation

Interpretable timbre synthesis using variational autoencoders regularized on timbre descriptors

Controllable timbre synthesis has been a subject of research for several decades, and deep neural networks have been the most successful in this area. Deep generative models such as Variational Autoencoders (VAEs) have the ability to generate a high-level representation of audio while providing a structured latent space. Despite their advantages, the interpretability of these latent spaces in terms of human perception is often limited. To address this limitation and enhance the control over timbre generation, we propose a regularized VAE-based latent space that incorporates timbre descriptors. Moreover, we suggest a more concise representation of sound by utilizing its harmonic content, in order to minimize the dimensionality of the latent space

An Exploration of the Latent Space of a Convolutional Variational Autoencoder for the Generation of Musical Instrument Tones

Variational Autoencoders (VAEs) constitute one of the most significant deep generative models for the creation of synthetic samples. In the field of audio synthesis, VAEs have been widely used for the generation of natural and expressive sounds, such as music or speech. However, VAEs are often considered black boxes and the attributes that contribute to the synthesis of a sound are yet unsolved. Existing research focused on the way input data can influence the generation of latent space, and how this latent space can create synthetic data, is still insufficient. In this manuscript, we investigate the interpretability of the latent space of VAEs and the impact of each attribute of this space on the generation of synthetic instrumental notes. The contribution to the body of knowledge of this research is to offer, for both the XAI and sound community, an approach for interpreting how the latent space generates new samples. This is based on sensitivity and feature ablation analyses, and descriptive statistics

A How-To Guide for Student Generated Video

The type of assessment used by the instructor is a major consideration that must be taken into account when designing a third level course. The importance of assessment can be understood if one frames it not only as assessment of learning but also as assessment for learning. In this new framework, in addition to measuring students’ knowledge of the material, assessment can be thought of as a tool used for providing feedback, for defining academic standards, and for directing student learning (Harris, 2005). There is currently a movement calling for a shift away from traditional high-stakes assessment towards alternative assessment practices based on the increasingly diverse student population, constructivist learning theory, and the need for more authentic evaluations of student performance (Anderson, 1998). Within this trend, it is important to consider the potential of technology. The use of student-generated videos as assessment tools can be one way to incorporate technology into the classroom when taking a blended learning approach. This can increase student motivation, improve attitudes and learning behaviors, and increase learning performance. Generating videos is a move from passive to active learning. This project aimed to produce a how-to guide for the creation of video assignments within a specific module. We intend this guide to serve as a resource for lectures to aid the students when using this innovative assessment method. The graphic nature of the resource makes it easy to follow and student-centred, especially when compared to existing resources which tend to be text-based and more difficult to follow. In addition, it is our hope that our guide can encourage uniformity, be reusable, and provide a clear process that students can follow when taking on video assessments

The Design of Student Training Resources to Enhance the Student Voice in Academic Quality Assurance and Quality Enhancement Processes

Without appropriate training and recognition, students – in particular Class Representatives – often struggle to engage fully with a University’s quality assurance and quality enhancement processes. Through the “Our Student Voice” project in Technological University Dublin (TU Dublin), a suite of digital training resources were designed to provide training for students to help develop the requisite knowledge and skills for effective participation there processes, thus strengthening student engagement and enhancing the student voice. The resources are organised into thirteen accessible episodes that each commence with an animated scenario that sets out key messages. The remainder of the episode provides detailed guidance for students and learning activities to help students develop their skillset. Upon completion of the learning activities, and having satisfactorily undertaken one of three specific student role in the quality processes, students can apply for recognition through a digital badge. The training resources and digital badges have been co-designed by a project team comprised of staff and students from across the University guided by best practice internationally. This paper describes the co-design process and presents a set of lessons learned that may assist other higher education institutions in enabling impactful student engagement in their academic quality assurance and quality enhancement processes

Factors Associated With Referring Close Contacts to an App With Individually-Tailored Vaccine Information

Background: Infants too young to be fully vaccinated are vulnerable to potentially deadly influenza and pertussis infections. The cocooning strategy limits this risk by vaccinating those likely to interact with the infant and mother during this vulnerable time, such as close friends and family members. Distribution of accurate and accessible vaccine information through existing social networks could be an important tool in increasing vaccine confidence and coverage. Methods: We surveyed 1095 pregnant women from diverse prenatal care practices in Georgia and Colorado. These women were surveyed through a mobile app to assess vaccine intentions, attitudes, beliefs, norms, and levels of trust, and then presented brief individually-tailored educational videos about maternal and infant vaccines and the cocooning strategy. They were then given the opportunity to refer up to six contacts to enroll in the app and receive similar vaccine education. Results: Twenty-eight percent of these women referred at least one contact, with an average of 2.67 contacts per referring woman. Most referrals (93%) were partners, parents, siblings, relatives, or close friends. Attitudinal constructs significantly associated with increased likelihood of referring contacts included: intention to receive maternal influenza vaccine, perceived safety of maternal Tdap vaccine, perceived efficacy of maternal influenza vaccine, perceived susceptibility to and severity of influenza during pregnancy, and trust in vaccine information from the Centers for Disease Control and Prevention (CDC) and academic institutions. Uncertainty about infant vaccine intentions was associated with decreased likelihood of referring contacts. Conclusions: Pregnant women who valued vaccination and trusted vaccine information from academic institutions were more likely to refer an educational app about vaccines than those who did not. Further research is needed to determine the potential impact of this strategy on vaccine coverage when implemented on a large scale. Trial Registration: The survey informing this article was part of a randomized controlled trial funded by the National Institutes of Health [clinicaltrials.gov registration number NCT02898688]

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead