Evaluation of Financial Trends and Fundraising Program of STAP

Every non-profit organization faces challenges with funding. This project examines fundraising trends and threats facing the Southern Tier AIDS Program (STAP). The project began out of concerns about the impact changes in Medicaid legacy rates and Governor Cuomo’s plan for the end of AIDS 2020. Government grants and Medicaid are the largest revenue streams for the organization, changes in these streams could have a devastating impact on the organization. Along with identifying the impact of the funding changes I will evaluate the current fundraising programs and make recommendations based on the past trends and projections of the impact of funding changes.https://orb.binghamton.edu/mpa_capstone/1007/thumbnail.jp

Precise Model for Small-Body Thermal Radiation Pressure Acting on Spacecraft

A precise representation of small-body surface thermal radiation pressure effects acting on orbiting spacecraft is discussed. The proposed framework takes advantage of a general Fourier series expansion to compute small-body surface thermal radiation pressure. Fourier series expansion has been used before for the precise representation of solar radiation pressure effects on spacecraft orbiting small bodies. This framework takes into account the geometric relationship of orbiting spacecraft with the small-body surface, surface thermal parameters of the small body, and the shape and surface properties of spacecraft allowing for the computation of thermal radiation pressure, which may also be used for the generation of precise orbit determination solutions. After presenting the general model, an example application of the model for the OSIRIS-REx spacecraft in orbit about Asteroid (101955) Bennu is provided. Simulation studies were used to evaluate the effect of mismodeling of thermal radiation pressure on the spacecraft and study the use of the proposed method for generating precise orbit determination solutions

A Novel Multi-Spacecraft Interplanetary Global Trajectory Optimization Transcription

As the frontier of space exploration continues to advance, so does the design complexity of future interplanetary missions. One avenue of this increasing complexity includes a class of designs known as "Distributed Spacecraft Missions"; missions where multiple spacecraft coordinate to perform shared objectives. Current approaches for the global trajectory optimization of these Multi-Vehicle Missions (MVMs) are prone to shortcomings including laborious iterative design, considerable human-in-the-loop effort, treatment of the multi-vehicle problem as multiple separate trajectory optimization subproblems (resulting in suboptimal solutions where the whole is less than the sum of its parts), and poor handling of coordination objectives and constraints. There are only a handful of software platforms in existence capable of fully-automated, rapid, interplanetary mission and systems global optimization including the Parallel Global Multiobjective Optimizer (PaGMO), the Gravity Assisted Low-thrust Local Optimization Program (GALLOP), and the Evolutionary Mission Trajectory Generator (EMTG). However, none of these tools is capable of performing such tasks for MVM designs. The work outlined in this paper lays the groundwork for a technique to begin addressing these shortcomings. We present a fully-automated technique which frames interplanetary MVMs as Multi-Objective, Multi-Agent Hybrid Optimal Control Problems (MOMA HOCP). First, the basic functionality of this technique is validated on the single-vehicle problem of reproducing the Cassini interplanetary cruise

Density Estimation for Entry Guidance Problems using Deep Learning

This work presents a deep-learning approach to estimate atmospheric density profiles for use in planetary entry guidance problems. A long short-term memory (LSTM) neural network is trained to learn the mapping between measurements available onboard an entry vehicle and the density profile through which it is flying. Measurements include the spherical state representation, Cartesian sensed acceleration components, and a surface-pressure measurement. Training data for the network is initially generated by performing a Monte Carlo analysis of an entry mission at Mars using the fully numerical predictor-corrector guidance (FNPEG) algorithm that utilizes an exponential density model, while the truth density profiles are sampled from MarsGRAM. A curriculum learning procedure is developed to refine the LSTM network's predictions for integration within the FNPEG algorithm. The trained LSTM is capable of both predicting the density profile through which the vehicle will fly and reconstructing the density profile through which it has already flown. The performance of the FNPEG algorithm is assessed for three different density estimation techniques: an exponential model, an exponential model augmented with a first-order fading-memory filter, and the LSTM network. Results demonstrate that using the LSTM model results in superior terminal accuracy compared to the other two techniques when considering both noisy and noiseless measurements.Comment: Currently under revision for the AIAA Journal of Guidance Control and Dynamic

Dismantling Rubble Pile Asteroids with AoES (Area-of-Effect Soft-bots)

Area-of-Effect Softbots (AoES) are soft-robotic spacecraft that are designed with a large, flexible surface area to leverage the dynamical environment at rubble pile asteroids. In particular, this surface area allows AoES to use adhesive forces, both naturally arising from van der Waals forces between the AoES and the asteroid regolith, and by using active electroadhesion, as well as using SRP forces to provide fuel free orbit and hopping trajectory control. The main purpose of the bus structure is to house a digging and launching mechanism that can liberate and launch asteroid regolith off the surface of the asteroid to be collected in orbit

A Multifaceted Device for Discreetly Acquiring Natural Behaviors of Children with Autism

Autism is a multifaceted neurological disorder that affects the four fundamental areas of sensory processing, communication mechanisms, social interaction skills, and whole child/self-esteem. The underlying mechanisms and symptoms of the disorder have been shown to largely vary from patient to patient, and therefore, a durable, effective therapy is best achieved through multifaceted, multidisciplinary approaches that allow a direct assessment of each individual’s behavior, both quantitatively and qualitatively. The aim of this project was to simulate, design, manufacture, and assess a device that can help cultivate sensory, social, communication, and motor skills in autistic children while being able to extract data of the child’s behavior that could be used by the therapist. Critical components of the toy involve auditory and visual stimulation, as well as interactive mechanisms to promote development. The most important features of the toy are hidden cameras that discreetly monitor the child’s reactions in order to provide analytical feedback mechanisms, allowing parents, caregivers, or therapists to monitor and evaluate the child’s learning and therapy. The performance of the toy was examined on 17 children with autism at two specialized centers for child with developmental disorders. The results showed that the device was found satisfactory by the majority of children as assessed by their willingness to spend time accomplishing the tasks on the device, as well as by captured videos of their natural reactions throughout. Furthermore, improved performance was observed on the same population of children who were tested multiple times, indicating the potential use of the toy for therapeutic and learning purposes.Faculty Sponsor: Danial Shahmirzad

Children\u27s Folklore

A collection of original essays by scholars from a variety of fields—including American studies, folklore, anthropology, psychology, sociology, and education—Children\u27s Folklore: A Source Book moves beyond traditional social-science views of child development. It reveals the complexity and artistry of interactions among children, challenging stereotypes of simple childhood innocence and conventional explanations of development that privilege sober and sensible adult outcomes. Instead, the play and lore of children is shown to be often disruptive, wayward, and irrational. The contributors variably con-sider and demonstrate contextual and textual ways of studying the folklore of children. Avoiding a narrow definition of the subject, they examine a variety of resources and approaches for studying, researching, and teaching it. These range from surveys of the history and literature of children\u27s folklore to methods of field research, studies of genres of lore, and attempts to capture children\u27s play and games.https://digitalcommons.usu.edu/usupress_pubs/1059/thumbnail.jp

Analytical shape uncertainties in the polyhedron gravity model

The exploration of small bodies in the Solar system and the ability to perform remote or in situ science is tied to the understanding of the dynamical environment of such objects. As such, the evaluation of the gravity field arising from small bodies is key to this understanding. However, remote observations can only produce shape estimates, from which only uncertain gravity fields can be computed. The current disconnect in the literature between the uncertainty in the shape and that of the gravity field properties is detrimental to small body science and robust mission design. In particular, the literature does not provide any quantitative means to capture this link in the polyhedron gravity model, one of the main gravity model representations. With this in mind, this paper derives the expressions of the first variations and partial derivatives in the potential, acceleration and slopes computed from the polyhedron gravity model with respect to the vertices of the underlying body. These formulae are then combined with a Gaussian description of the uncertainty in the vertex coordinates so as to obtain analytical predictions of the potential, slope variances as well as the covariance in the acceleration at arbitrary locations around the body, treated as a stochastic shape. This linearized analytical approach was able to capture the statistical variation in the dynamical environment about asteroid 25143 Itokawa and 16 Psyche under the assumption of stochastic errors in the bodies’ shape models, at a lower computational cost than Monte–Carlo simulations. These methods should be of benefit to planetary scientists and mission designers seeking for more insight into the dynamical environment of uncertain small body shapes