2023 JSU Student Symposium Proceedings

https://digitalcommons.jsu.edu/ce_jsustudentsymp_2023/1062/thumbnail.jp

An Efficient Machine Learning Software Architecture for Internet of Things

Internet of Things (IoT) software is becoming a critical infrastructure for many domains. In IoT, sensors monitor their environment and transfer readings to cloud, where Machine Learning (ML) provides insights to decision-makers. In the healthcare domain, the IoT software designers have to consider privacy, real-time performance and cost in addition to ML accuracy. We propose an architecture that decomposes the ML lifecycle into components for deployment on a two-tier cloud, edge-core. It enables IoT time-series data to be consumed by ML models on edge-core infrastructure, with pipeline elements deployed on any tier, dynamically. The architecture feasibility and ML accuracy are validated with three brain-computer interfaces (BCI) based use-cases. The contributions are two-fold: first, we propose a novel ML-IoT pipeline software architecture that encompasses essential components from data ingestion to runtime use of ML models; second, we assess the software on cognitive applications and achieve promising results in comparison to literature

Addressing Energy Efficiency in System Design: A Journey FromArchitecture to Operation

Digital-transformation initiatives have led to major efficiencies and cost savings but at the cost of consuming nearly 10 percent of the world’s electricity. Energy consumption research has increased datacentre, network, and hardware efficiency, but a neglected aspect of energy research has been the energy consumption of the software applications that underpin digital transformation. To date, software architects have lacked the knowledge, guidance, and tools to allow them to understand the energy properties of their systems. The research reported in this thesis begins to address this situation by developing practical knowledge, techniques, and tools to allow software architects to play their part in controlling the energy consumption of our modern digital world. The work commences with an investigation into formal architectural description languages, through a literature review and a case study, resulting in two research contributions, namely a comprehensive systematic survey of architecture description languages from 1991 to 2015, and a case study of practical ADL use at scale in industry. The second part of the research investigates how to assist architects in prioritising energy efficiency through a study of how experienced architects focus their attention for maximum effectiveness, which leads to the development of a model to guide architecture practitioners, which is validated and refined through a large survey of practising software architects. The research contribution is a refined and validated model for architectural effort prioritisation. The third aspect of the research examines the energy-related guidance available to architects and having found little generally applicable advice, analyses a significant industrial case study to understand how leading-edge practitioners addressed energy efficiency, contributing a set of three energy-related architectural principles, which can be used to guide architects in improving application energy efficiency. Finally, we consider the practical problem of understanding the runtime energy properties of a system, and designed a novel approach to estimate the energy consumption of execution scenarios via application execution tracing and a cost-based energy model. We created a proof of concept implementation of the approach and validated its consistency and correctness through practical testing. The contribution of this work was twofold, namely the design of a practical system for allocating energy to application execution scenarios, and a tested, open-source, proof-of-concept implementation of the system. Hence, the result of this work is six distinct contributions to knowledge in the area of ADLs (the survey and practical case study), architectural practice (the prioritisation model and the architectural principles for energy efficiency) and application energy efficiency (the design of the energy allocation system and the proof-of-concept implementation), which collectively can help architects to treat energy efficiency as a first class architectural concern in their work

eduGraph: A Dashboard for Personalised Feedback in Massive Open Online Courses

Learning Analytics is concerned with the design and implementation of tools and processes for collecting, analysing, and communicating information about teaching and learning. It is enabled by data, but not driven by it, rather it tries to empower human judgements by presenting meaningful facts. This thesis explores the data generated in Open edX courses to understand how it can be analysed and used to impact learners' motivation in online courses. It is carried out using Design Science, a research methodology aiming to produce artefacts that can improve the interaction with problems. In this thesis I present the eduGraph dashboard, a dashboard that uses Learning Analytics to present meaningful insights about learners' learning process in Massive Open Online Courses (MOOCs). Results indicate that learners perceive the dashboard as useful and effective at motivating them to take part in online courses, and that it enables them to keep track of their progress in the courses. I posit that the biggest problem facing Learning Analytics today are the lack of accessible data, and that it is possible for reasearchers to create more accurate learner models by using Learning Anaytics theories and methods in combination with the iterative and technical process of Information Systems development.Masteroppgave i informasjonsvitenskapINFO390MASV-INF

A Design-Science-Research Approach

Neue Organisationsformen, wie evolutionäre Organisationen, bilden in vielen Kooperationsszenarien sozio-technische Konstrukte mit modernen CSCW Anwendungen aus. Daher erfordern Veränderungen dieser sozialen Systeme eine kontinuierliche Anpassung der technischen Tools an die neuen sozialen Konfigurationen. Diese Dissertation ist als Design Science Research (DSR) Projekt konzipiert und addressiert die folgende Forschungsfrage (RQ): “Wie können soziotechnische, evolutionäre Organisationen die Herausforderungen der joint optimization und des organizational choice während ihrer autopoietischen Veränderungsprozesse addressieren?” Die Fallstudie Viva con Agua de St. Pauli e.V. wurde mittels qualitativer und ethnographischer Methoden im Rahmen der entsprechenden DSR Zyklen untersucht. Das Forschungsprojekt fokussiert die Entwicklung von Artefakten indem sowohl eine technische, als auch eine soziale Perspektive eingenommen wird. Aus der technische Perspektive wird die RQ durch eine Microservice-Plattform adressiert. Die Architektur dient der Verteilung von Verantwortlichkeit für die Software in einem heterogenen Netzwerk von Entwickler:innen. Dabei müssen diverse neue Herausforderungen beachtet werden, wie etwa die Verteilung des User Interface. Durch die Betrachtung der RQ aus der sozialen Perspektive wird der USMU Workshop entwickelt. Dieses Artefakt dient der Verbindung der Charakteristika evolutionärer Organisationen mit agiler Software Entwicklung und mit Methoden des partizipativen Designs. Die Studien zeigen, dass beide Artefakte die RQ adressieren. Zudem konnte ich für beide Artefakte wertvolle Verbesserungsmöglichkeiten aufzeigen. Somit motivieren die Ergebnisse den nächsten Schritt des Projekts und die vorliegende Thesis wird Bestandteil des zyklischen Ablaufs eines DSR Projekts.The emergence of new types of organizational structures, such as evolutionary-teal organizations, almost always leads to the development of socio-technical constructs when it comes to working in collaboration with modern CSCW applications. A consequence of this is that the social system’s autopoietic change processes create challenges that compel one to adjust the implementation of the technical tool to the social system’s new configuration. This thesis is structured according to the design science research (DSR) approach and focuses on the research question (RQ): “How can socio-technical evolutionary-teal organizations address the challenges of joint optimization and organizational choice during their autopoietic processes?” For this purpose, the case study Viva con Agua de St. Pauli e.V. is investigated using a qualitative ethnographical approach during the DSR cycles. Addressing the RQ, two artifacts are designed from a technical as well as a social perspective. While the technical perspective primarily investigates the adjustments of technology, the social perspective focuses on the management of change in socio-technical evolutionary-teal organizations. I propose a microservice platform as an artifact that addresses the RQ from a technical perspective. The microservice architecture aims at spreading the responsibility for the software through a heterogeneous ecosystem of developers. The newly designed USMU workshop is addressing the RQ from the social perspective. It strives to intertwine the characteristics of evolutionary-teal organizations with agile software development and participatory design methods. In my studies, I examine the fact that both artifacts can be used to address the RQ. Additionally, I was able to identify valuable improvements for both of my artifacts. Hence, the project follows the lifecycle of a DSR project by reasoning through the results presented here for its next iteration

McNair Scholars Research Journal Volume XII

https://commons.stmarytx.edu/msrj/1011/thumbnail.jp

McNair Scholars Research Journal Volume XII

https://commons.stmarytx.edu/msrj/1011/thumbnail.jp