2022 Dissertations (UMKC)
https://hdl.handle.net/10355/89681
2024-03-28T17:18:54ZA Cross-Case Study: The Personal and Professional Challenges Experienced by Nurse Educators at Three Midwestern Colleges and Universities During the Covid-19 Pandemic
https://hdl.handle.net/10355/91314
A Cross-Case Study: The Personal and Professional Challenges Experienced by Nurse Educators at Three Midwestern Colleges and Universities During the Covid-19 Pandemic
Woolston, Wendy
The COVID-19 pandemic has had a profound effect on the educational system in the United States, especially nursing. Nurse educators are essential to educating the next generation of nurses, but they are in short supply while the need for nurses is growing. There is limited research on the impact that the COVID-19 pandemic has had on nurse educators’ wellbeing. The purpose of this study was to explore the personal and professional challenges of being an academic nurse educator during the COVID-19 pandemic and the impact of this transition on their lives and academic nursing in the future. The research questions were (1) How do nurse educators describe the pedagogical challenges encountered when changing the format of nursing education as a result of the COVID-19 pandemic? (2) How do nurse educators describe the effects of the pedagogical challenges (when changing the format of nursing education) encountered and institutional constraints due to the COVID-19 pandemic on their personal wellbeing? (3) How do nurse educators believe their personal and professional challenges, through experiencing the COVID-19 pandemic, may impact academic nursing education going forward? The theoretical lens used to guide the study was Hardy and Conway’s Role Theory and Schoening’s Nurse Educator Transition (NET) model.
The study design was a qualitative multiple-case, descriptive study employing a cross-case analysis of five nurse educator’s individual interviews and documents employed at three baccalaureate nursing programs. Each nurse educator’s case was individually presented and analyzed, then cross-analyzed. From the cross-analysis eight themes and five sub-themes where developed. The eight themes identified were (1) the Covid-19 pandemic resulted in pedagogical changes by the nurse educator to meet the course and student learning objectives; (2) nurse educators experienced tension over ethical issues that resulted in disunity; (3) institutional communication plays an important role in nurse educator satisfaction; (4) nurse educators struggled to balance educator role and home/life responsibilities; (5) nurse educators emotional and physical wellbeing declined due to educator role demands; (6) nurse educators are proud of their own and their student’s resiliency; (7) student success became the nurse educator’s responsibility and; (8) future academic nursing will change.
Title from PDF of title page, viewed August 22, 2022; Dissertation advisor: Tiffani Riggers-Piehl; Vita; Includes bibliographical references (pages 303-317); Dissertation (Ed.D)--School of Education. University of Missouri--Kansas City, 2022
2022-01-01T00:00:00ZA Cubic Spline Projection Method for Computing Stationary Density Functions of Frobenius-Perron Operator
https://hdl.handle.net/10355/91309
A Cubic Spline Projection Method for Computing Stationary Density Functions of Frobenius-Perron Operator
Alshekhi, Azzah Ahmed
Stationary density functions of Frobenius-Perron operators have critical applications in many fields of science and engineering. Accordingly, approximating stationary density functions f* is important and the focus of this dissertation. Among the computational methods of approximating the smooth f*, the linear spline and quadratic spline projection methods have been proven effective. However, we intend to improve the convergence rate of the previous methods. We will fulfill this goal by using cubic spline functions since cubic spline functions are twice continuously differentiable on the whole domain. Theoretically, we prove the existence of a nonzero sequence of cubic spline functions {fₙ} that converges to the stationary density function f* of the Frobenius-Perron operator in L¹-norm. The numerical experimental results assure that the cubic spline projection method gives the fastest convergence rate so far. In addition, when the stationary density function f* lies in the cubic spline space, the cubic spline projection method computes f* exactly no matter what n may be.
Title from PDF of title page, viewed August 22, 2022; Dissertation (Ph.D)--Department of Mathematics and Statistics, Department of Physics and Astronomy. University of Missouri--Kansas City, 2022; Includes bibliographical references (pages 143-150)
2022-01-01T00:00:00ZA Faint Light
https://hdl.handle.net/10355/93863
A Faint Light
Shi, Lan
My orchestra piece, A Faint Light, has an introduction, five sections (Entering the mountain, The battle of ghosts I, Asking the God of the mountain, The battle of ghosts II, and The answer to the heart), and a coda. It consists of two main musical materials: a dance-like motive with irregular accents, and a pentatonic thematic melody. The two materials have been developed throughout the piece. The motive was derived from a sacrifice dance from Yunnan, a province located in southwest China. The thematic melody was inspired by a Chinese fairy tale about a recluse named Han Guang. In Chinese, Han Guang also means a faint light, which became the title of this work. I was impressed by the faith of the recluse in the story. He persisted in the path he chose even though he knew that the faith he pursued would never come true. I used pointillistic writing techniques in juxtaposed multi-layers and imitated the performing skills of Chinese plucking instruments in the strings. To highlight the images of each section, I used different percussion instruments respectively. For example, in the second and the fourth sections to describe the fighting scene, I used a snare drum, tom-toms, and bass drum. In the third section, I used sistrum and woodblocks to express the atmosphere of Zen. While the imagination of the fairy tale scene was portrayed in the introduction and the coda, the seed of the thematic melodic material was planted in the first section. The complete melody was initiated in the third section with strings. The further development of the melodic material brought in thicker and richer textures in the fifth section with intensive counterparts, until the climax was reached in orchestra tutti before the peaceful coda brought in, recalling the atmosphere of Zen depicted at the beginning of the piece.
Title from PDF of title page, viewed February 9, 2003; Dissertation advisor: Zhou Long; Vita; Dissertation (D.M.A.)--UMKC Conservatory. University of Missouri--Kansas City, 2022
2022-01-01T00:00:00ZA Hardware/Software Co-integration Approach for Securing Network
Infrastructure using Reconfigurable Computing
https://hdl.handle.net/10355/91461
A Hardware/Software Co-integration Approach for Securing Network
Infrastructure using Reconfigurable Computing
Danesh, Wafi
In the last two decades, there has been a rapid proliferation of connected devices spanning various application domains. Coupled with the rise of novel computer networking paradigms, such as Internet-of-Things (IoT), edge computing, fog computing, cloud computing among others, experts predicted an estimated 50 billion connected devices by the year 2020. The emergence of these networking paradigms, however, raises critical security vulnerabilities. Such vulnerabilities, as a result, exposes new attack vectors to exploitation by increasingly competent attackers, with ever more sophisticated means at their disposal, at both the software and hardware level.
The key reasons for the existence of such vulnerabilities in modern computer networks, arise due to the multifaceted constraints that need to be incorporated. Many current networking applications work under operating conditions of severe cost, power, and resource constraints. As a consequence of these constraints, the requisite computational resources required to incorporate critical security countermeasures are significantly reduced. Developers and system designers for the varied modern computer networking systems are often forced into a tradeoff of conventional security features, such as encryption, authentication, access control, network, and access security. At the software level, these vulnerabilities manifest in the form of unforeseen network intrusions, such as zero-day attacks. At the hardware level, a very serious threat are hardware Trojans (HT), which are clandestine, malicious circuits that can be inserted during runtime in the network infrastructure.
In this dissertation, two key security countermeasures are proposed against vulnerabilities at both the hardware and software levels. Based on these countermeasures, an attempt is made to synthesize both countermeasures and propose a unified security paradigm, which can tackle both threat scenarios simultaneously. At the hardware level, this dissertation focuses on the serious threat posed by hardware Trojan (HT) insertion in the field programmable gate array (FPGA) configuration bitstream. Low-end FPGAs are widely used in networking infrastructure and forego critical security features such as encryption of bitstreams to optimize resource constrained deployment. An attacker can reverse engineer the configuration bitstream to insert HTs, which are clandestine malicious circuits, in the FPGA. The proposed countermeasure uses bitstream reverse engineering to perform HT detection and is scalable to any circuit size and topology. With regards to the software level, this dissertation focuses on the vulnerability of deep learning (DL) based network intrusion detection to adversarial examples in IoT networks. Even though DL approaches have proven extremely effective in intrusion detection given the high volume of network traffic in modern IoT networks, DL models are prone to misclassification to minute perturbations in input samples, called adversarial examples. In this dissertation, an unsupervised adversarial example detection approach is proposed which does not require extra hardware overhead for implementation and is based on the intrinsic characteristics of the DL model implemented.
As an additional research focus, this dissertation investigates the use of multi-valued logic (MVL) in a circuit decomposition and synthesis approach for beyond Moore circuit implementations. MVL computing provides a larger information capacity compared to binary CMOS logic and is suitable for providing efficient data compression, processing, and communication with the massive network traffic volumes in modern computer networks. Some of the key issues preventing widespread adoption of MVL computing are the complex MVL expressions obtained from traditional logic decomposition approaches and the inefficient usage of binary switches for MVL data representation, communication, and processing. Therefore, this dissertation proposes a logic decomposition and synthesis algorithm for MVL, which combines concepts from machine learning and nanoelectronics. The proposed algorithm decomposes a MVL function to a set of linear expressions implemented by simple output summations, is adaptable to any device technology and radix of representation, and scalable with circuit size and topology. Compared to other popular MVL decomposition methods, the proposed algorithm presents significant savings in hardware overhead and computational complexity. In recent years, small but significant research efforts have been dedicated to usage of MVL in DL classifier design and HT detection. These innovations can pave the way for integrating MVL approaches in the security context at both the hardware and software level. In summary, this dissertation provides a detailed investigation of key security vulnerabilities at the software and hardware levels for modern computer networks, proposes adept and effective countermeasures and in addition, provides a proof-of-concept for a MVL decomposition and synthesis approach for beyond Moore circuits.
Title from PDF of title page, viewed September 14, 2022; Dissertation advisor: Mostafizur Rahman; Vita; Includes bibliographical references (pages 68-85); Dissertation (Ph.D)--Department of Computer Science and Electrical Engineering. University of Missouri--Kansas City, 2022
2022-01-01T00:00:00Z