Design & Develop A Satellite Telemetry Display Application

The purpose of this thesis project is to design and implement an extensible and adaptable GUI for viewing satellite telemetry. The software available today to view satellite telemetry is very crude, hard to understand, and is not very reliable. Software is usually built from scratch for each new satellite system. This project will build a GUI that can be used to display all types of satellite telemetry. The GUI will be built in Java, have an easy to use interface, and be very customizable. The GUI will allow users to run the software on Windows and UNIX based operating systems. It will allow the user to set up the telemetry viewing pages as he or she fits. The goals for this project are to design and build the software application

Cloud Based IoT Architecture

The Internet of Things (IoT) and cloud computing have grown in popularity over the past decade as the internet becomes faster and more ubiquitous. Cloud platforms are well suited to handle IoT systems as they are accessible and resilient, and they provide a scalable solution to store and analyze large amounts of IoT data. IoT applications are complex software systems and software developers need to have a thorough understanding of the capabilities, limitations, architecture, and design patterns of cloud platforms and cloud-based IoT tools to build an efficient, maintainable, and customizable IoT application. As the IoT landscape is constantly changing, research into cloud-based IoT platforms is either lacking or out of date. The goal of this thesis is to describe the basic components and requirements for a cloud-based IoT platform, to provide useful insights and experiences in implementing a cloud-based IoT solution using Microsoft Azure, and to discuss some of the shortcomings when combining IoT with a cloud platform

Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

Cross-feature trained machine learning models for QoT-estimation in optical networks

The ever-increasing demand for global internet traffic, together with evolving concepts of software-defined networks and elastic-optical-networks, demand not only the total capacity utilization of underlying infrastructure but also a dynamic, flexible, and transparent optical network. In general, worst-case assumptions are utilized to calculate the quality of transmission (QoT) with provisioning of high-margin requirements. Thus, precise estimation of the QoT for the lightpath (LP) establishment is crucial for reducing the provisioning margins. We propose and compare several data-driven machine learning (ML) models to make an accurate calculation of the QoT before the actual establishment of the LP in an unseen network. The proposed models are trained on the data acquired from an already established LP of a completely different network. The metric considered to evaluate the QoT of the LP is the generalized signal-to-noise ratio (GSNR), which accumulates the impact of both nonlinear interference and amplified spontaneous emission noise. The dataset is generated synthetically using a well-tested GNPy simulation tool. Promising results are achieved, showing that the proposed neural network considerably minimizes the GSNR uncertainty and, consequently, the provisioning margin. Furthermore, we also analyze the impact of cross-features and relevant features training on the proposed ML models’ performance

Annotated bibliography of software engineering laboratory literature

An annotated bibliography is presented of technical papers, documents, and memorandums produced by or related to the Software Engineering Laboratory. The bibliography was updated and reorganized substantially since the original version (SEL-82-006, November 1982). All materials were grouped into eight general subject areas for easy reference: (1) The Software Engineering Laboratory; (2) The Software Engineering Laboratory: Software Development Documents; (3) Software Tools; (4) Software Models; (5) Software Measurement; (6) Technology Evaluations; (7) Ada Technology; and (8) Data Collection. Subject and author indexes further classify these documents by specific topic and individual author

Annotated bibliography of software engineering laboratory literature

An annotated bibliography of technical papers, documents, and memorandums produced by or related to the Software Engineering Laboratory is given. More than 100 publications are summarized. These publications cover many areas of software engineering and range from research reports to software documentation. This document has been updated and reorganized substantially since the original version (SEL-82-006, November 1982). All materials have been grouped into eight general subject areas for easy reference: the Software Engineering Laboratory; the Software Engineering Laboratory-software development documents; software tools; software models; software measurement; technology evaluations; Ada technology; and data collection. Subject and author indexes further classify these documents by specific topic and individual author

Annotated bibliography of Software Engineering Laboratory literature

An annotated bibliography of technical papers, documents, and memorandums produced by or related to the Software Engineering Laboratory is given. More than 100 publications are summarized. These publications cover many areas of software engineering and range from research reports to software documentation. All materials have been grouped into eight general subject areas for easy reference: The Software Engineering Laboratory; The Software Engineering Laboratory: Software Development Documents; Software Tools; Software Models; Software Measurement; Technology Evaluations; Ada Technology; and Data Collection. Subject and author indexes further classify these documents by specific topic and individual author