Perceptions of co-teaching in the middle school English language arts classroom

The purpose of this research study was to investigate the perceptions of the co-teaching model in the middle school English Language Arts classroom. Data was kept over a three-week period and tracked through individual interviews with teachers in the English Language Arts department. Each interview included the same number of questions with the same prompts. These questions led teachers to discuss their experiences implementing co-teaching, working with a co-teacher and the time and effort that went into the process. As a result of the data collected, I was able to analyze the findings into specific themes including the roles and responsibilities in the co-teaching classroom, issues of co-planning, and the co-teaching relationship. These major themes were then further examined and related themes emerged such as control, lack of co-planning time, inappropriate pairing, different personalities, the uncertainty of future partnerships and the importance of trust and respect. It was concluded that lack of communication existed the most among co-teachers in the areas of responsibility, co-planning and in the co-teaching relationship

Characterization and Commissioning of a Ka-Band Ground Station for Cognitive Algorithm Development

In 2018, the Cognitive Communications and Propagation projects completed installation and checkout testing of a new Ka-Band ground station at the NASA Glenn Research Center in Cleveland, Ohio. The Cognitive Algorithms Demonstration Testbed (CADeT) was developed to provide a fully characterized and controllable dynamic link environment to researchers looking to demonstrate hardware and software aligned with atmospheric sensing and cognitive algorithms. CADeT integrates a host of precision control and measurement systems in addition to repurposing a 5.5 meter beam-waveguide dish platform previously used with the Advanced Communications Technology Satellite (ACTS). This paper will discuss the laboratory testing of ground station components with a emphasis on elements vital to achieving link budget requirements including characterization of the new Gallium Nitride (GaN) Solid State Power Amplifier (SSPA) and far-field measurements of the new antenna feed. Finally, the paper discusses in-situ tests conducted with CADeT and the Tracking and Data Relay Satellite System (TDRSS) to validate laboratory results and make necessary link budget adjustments before reviewing the lessons learned

Random strings and tt-degrees of Turing complete C.E. sets

We investigate the truth-table degrees of (co-)c.e.\ sets, in particular, sets of random strings. It is known that the set of random strings with respect to any universal prefix-free machine is Turing complete, but that truth-table completeness depends on the choice of universal machine. We show that for such sets of random strings, any finite set of their truth-table degrees do not meet to the degree~0, even within the c.e. truth-table degrees, but when taking the meet over all such truth-table degrees, the infinite meet is indeed~0. The latter result proves a conjecture of Allender, Friedman and Gasarch. We also show that there are two Turing complete c.e. sets whose truth-table degrees form a minimal pair.Comment: 25 page

A Communication Channel Density Estimating Generative Adversarial Network

Autoencoder-based communication systems use neural network channel models to backwardly propagate message reconstruction error gradients across an approximation of the physical communication channel. In this work, we develop and test a new generative adversarial network (GAN) architecture for the purpose of training a stochastic channel approximating neural network. In previous research, investigators have focused on additive white Gaussian noise (AWGN) channels and/or simplified Rayleigh fading channels, both of which are linear and have well defined analytic solutions. Given that training a neural network is computationally expensive, channel approximation networks and more generally the autoencoder systemsshould be evaluated in communication environments that are traditionally difficult. To that end, our investigation focuses on channels that contain a combination of non-linear amplifier distortion, pulse shape filtering, intersymbol interference, frequency-dependent group delay, multipath, and non-Gaussian statistics. Each of our models are trained without any prior knowledge of the channel. We show that the trained models have learned to generalize over an arbitrary amplifier drive level and constellation alphabet. We demonstrate the versatility of our GAN architecture by comparing the marginal probability density function of several channel simulations with that of their corresponding neural network approximation

On-Orbit Validation of a Framework for Spacecraft-Initiated Communication Service Requests with NASA's SCaN Testbed

We design, analyze, and experimentally validate a framework for demand-based allocation of high-performance space communication service in which the user spacecraft itself initiates a request for service. Leveraging machine-to-machine communications, the automated process has potential to improve the responsiveness and efficiency of space network operations. We propose an augmented ground station architecture in which a hemispherical-pattern antenna allows for reception of service requests sent from any user spacecraft within view. A suite of ground-based automation software acts upon these direct-to-Earth requests and allocates access to high-performance service through a ground station or relay satellite in response to immediate user demand. A software-defined radio transceiver, optimized for reception of weak signals from the helical antenna, is presented. Design and testing of signal processing equipment and a software framework to handle service requests is discussed. Preliminary results from on-orbit demonstrations with a testbed onboard the International Space Station are presented to verify feasibility of the concept

STRS Compliant FPGA Waveform Development

The Space Telecommunications Radio System (STRS) Architecture Standard describes a standard for NASA space software defined radios (SDRs). It provides a common framework that can be used to develop and operate a space SDR in a reconfigurable and reprogrammable manner. One goal of the STRS Architecture is to promote waveform reuse among multiple software defined radios. Many space domain waveforms are designed to run in the special signal processing (SSP) hardware. However, the STRS Architecture is currently incomplete in defining a standard for designing waveforms in the SSP hardware. Therefore, the STRS Architecture needs to be extended to encompass waveform development in the SSP hardware. The extension of STRS to the SSP hardware will promote easier waveform reconfiguration and reuse. A transmit waveform for space applications was developed to determine ways to extend the STRS Architecture to a field programmable gate array (FPGA). These extensions include a standard hardware abstraction layer for FPGAs and a standard interface between waveform functions running inside a FPGA. A FPGA-based transmit waveform implementation of the proposed standard interfaces on a laboratory breadboard SDR will be discussed

Modulation Classification of Satellite Communication Signals Using Cumulants and Neural Networks

National Aeronautics and Space Administration (NASA)'s future communication architecture is evaluating cognitive technologies and increased system intelligence. These technologies are expected to reduce the operational complexity of the network, increase science data return, and reduce interference to self and others. In order to increase situational awareness, signal classification algorithms could be applied to identify users and distinguish sources of interference. A significant amount of previous work has been done in the area of automatic signal classification for military and commercial applications. As a preliminary step, we seek to develop a system with the ability to discern signals typically encountered in satellite communication. Proposed is an automatic modulation classifier which utilizes higher order statistics (cumulants) and an estimate of the signal-to-noise ratio. These features are extracted from baseband symbols and then processed by a neural network for classification. The modulation types considered are phase-shift keying (PSK), amplitude and phase-shift keying (APSK),and quadrature amplitude modulation (QAM). Physical layer properties specific to the Digital Video Broadcasting - Satellite- Second Generation (DVB-S2) standard, such as pilots and variable ring ratios, are also considered. This paper will provide simulation results of a candidate modulation classifier, and performance will be evaluated over a range of signal-to-noise ratios, frequency offsets, and nonlinear amplifier distortions

Interference Mitigation Using Cyclic Autocorrelation and Multi-Objective Optimization

Radio frequency interference on space-to-ground communications links can degrade performance and disrupt the transfer of critical data. These interference events become increasingly likely as more users enter the spectrum, due in part to shared spectrum allocations and scheduling conflicts. If this interference could be detected and mitigated by an automated system, then link performance and reliability in these scenarios could be improved. This report describes the implementation and evaluation of an automated interference mitigation system that provides this functionality. The system uses Cyclic Autocorrelation (CAC) signal processing techniques to monitor the spectrum and detect interfering signals, and it applies a multi-objective optimization approach to mitigate interference by changing link parameters to continuously optimize the link. The implementation was evaluated to characterize its signal detection capabilities for various link qualities and to compare its link management performance to Adaptive Coding and Modulation (ACM) and Constant Coding and Modulation (CCM) when in the presence of randomized interference. In the latter evaluation, the interference mitigation system achieved the highest average throughput in each tested scenario. With these results, the proposed solution provides the groundwork for further automated link management capabilities and continued investigation into interference mitigation approaches

Pre-Flight Testing and Performance of a Ka-Band Software Defined Radio

National Aeronautics and Space Administration (NASA) has developed a space-qualified, reprogrammable, Ka-band Software Defined Radio (SDR) to be utilized as part of an on-orbit, reconfigurable testbed. The testbed will operate on the truss of the International Space Station beginning in late 2012. Three unique SDRs comprise the testbed, and each radio is compliant to the Space Telecommunications Radio System (STRS) Architecture Standard. The testbed provides NASA, industry, other Government agencies, and academic partners the opportunity to develop communications, navigation, and networking applications in the laboratory and space environment, while at the same time advancing SDR technology, reducing risk, and enabling future mission capability. Designed and built by Harris Corporation, the Ka-band SDR is NASA's first space-qualified Ka-band SDR transceiver. The Harris SDR will also mark the first NASA user of the Ka-band capabilities of the Tracking Data and Relay Satellite System (TDRSS) for on-orbit operations. This paper describes the testbed's Ka-band System, including the SDR, travelling wave tube amplifier (TWTA), and antenna system. The reconfigurable aspects of the system enabled by SDR technology are discussed and the Ka-band system performance is presented as measured during extensive pre-flight testing