Computer Engineering Commons^™

Our Future Arrived: Diffusion Of Human-Machine Communication And Transformation Of The World For The Post-Pandemic Era, Do Kyun David Kim, Gary Kreps, Rukhsana Ahmed

Human-Machine Communication

The world is getting into a new phase in history. For the first time, humans are verbally communicating and developing meaningful relationships with non-living objects. AI is a wormhole to open a gateway to the new world, and the COVID-19 pandemic prepared the world to transform its system to be an open system that responds to, communicates with, and utilizes the remnants coming out of the wormhole of the new world. Now, we urgently need to create a holistic discourse on how we can recognize, develop, or shape the identities of communicable machines as people develop a partnership with them. …

Performance Enhancement Of Time Delay And Convolutional Neural Networks Employing Sparse Representation In The Transform Domains, Masoumeh Kalantari Khandani

Electronic Theses and Dissertations, 2020-2023

Deep neural networks are quickly advancing and increasingly used in many applications; however, these networks are often extremely large and require computing and storage power beyond what is available in most embedded and sensor devices. For example, IoT (Internet of Things) devices lack powerful processors or graphical processing units (GPUs) that are commonly used in deep networks. Given the very large-scale deployment of such low power devices, it is desirable to design methods for efficient reduction of computational needs of neural networks. This can be done by reducing input data size or network sizes. Expectedly, such reduction comes at the …

Human-Machine Communication: Complete Volume. Volume 2

Human-Machine Communication

This is the complete volume of HMC Volume 2.

Social Robots As The Bride? Understanding The Construction Of Gender In A Japanese Social Robot Product, Jindong Liu

Human-Machine Communication

This study critically investigates the construction of gender on a Japanese hologram animestyle social robot Azuma Hikari. By applying a mixed method merging the visual semiotic method and heterogeneous engineering approach in software studies, the signs in Azuma Hikari’s anthropomorphized image and the interactivity enabled by the multimedia interface have been analyzed and discussed. The analysis revealed a stereotyped representation of a Japanese “ideal bride” who should be cute, sexy, comforting, good at housework, and subordinated to “Master”-like husband. Moreover, the device interface disciplines users to play the role of “wage earner” in the simulated marriage and reconstructs the gender …

Forms And Frames: Mind, Morality, And Trust In Robots Across Prototypical Interactions, Jaime Banks, Kevin Koban, Philippe De V. Chauveau

Human-Machine Communication

People often engage human-interaction schemas in human-robot interactions, so notions of prototypicality are useful in examining how interactions’ formal features shape perceptions of social robots. We argue for a typology of three higher-order interaction forms (social, task, play) comprising identifiable-but-variable patterns in agents, content, structures, outcomes, context, norms. From that ground, we examined whether participants’ judgments about a social robot (mind, morality, and trust perceptions) differed across prototypical interactions. Findings indicate interaction forms somewhat influence trust but not mind or morality evaluations. However, how participants perceived interactions (independent of form) were more impactful. In particular, perceived task interactions fostered functional …

Moving Ahead With Human-Machine Communication, Leopoldina Fortunati, Autumn P. Edwards

Human-Machine Communication

In this essay, we introduce the 10 articles comprising Volume 2 (2021) of Human-Machine Communication, each of which is innovative and offers a substantial contribution to the field of human-machine communication (HMC). As a collection, these articles move forward the HMC project by touching on four layers of important discourse: (1) updates to theoretical frameworks and paradigms, including Computers as Social Actors (CASA), (2) examination of ontology and prototyping processes, (3) critical analysis of gender and ability/disability relations, and (4) extension of HMC scholarship into organizational contexts. Building upon the insights offered by the contributing authors and incorporating perspectives …

Fpga-Augmented Secure Crash-Consistent Non-Volatile Memory, Yu Zou

Electronic Theses and Dissertations, 2020-2023

Emerging byte-addressable Non-Volatile Memory (NVM) technology, although promising superior memory density and ultra-low energy consumption, poses unique challenges to achieving persistent data privacy and computing security, both of which are critically important to the embedded and IoT applications. Specifically, to successfully restore NVMs to their working states after unexpected system crashes or power failure, maintaining and recovering all the necessary security-related metadata can severely increase memory traffic, degrade runtime performance, exacerbate write endurance problem, and demand costly hardware changes to off-the-shelf processors. In this thesis, we summarize and expand upon two of our innovative works, ARES and HERMES, to design …

Improving Performance And Flexibility Of Fabric-Attached Memory Systems, Vamsee Reddy Kommareddy

Electronic Theses and Dissertations, 2020-2023

As demands for memory-intensive applications continue to grow, the memory capacity of each computing node is expected to grow at a similar pace. In high-performance computing (HPC) systems, the memory capacity per compute node is decided upon the most demanding application that would likely run on such a system, and hence the average capacity per node in future HPC systems is expected to grow significantly. However, diverse applications run on HPC systems with different memory requirements and memory utilization can fluctuate widely from one application to another. Since memory modules are private for a corresponding computing node, a large percentage …

Long Short-Term Memory With Spin-Based Binary And Non-Binary Neurons, Meghana Reddy Vangala

Electronic Theses and Dissertations, 2020-2023

Research in the field of neural networks has shown advancement in the device technology and machine learning application platforms of use. Some of the major applications of neural network prominent in recent scenarios include image recognition, machine translation, text classification and object categorization. With these advancements, there is a need for more energy-efficient and low area overhead circuits in the hardware implementations. Previous works have concentrated primarily on CMOS technology-based implementations which can face challenges of high energy consumption, memory wall, and volatility complications for standby modes. We herein developed a low-power and area-efficient hardware implementation for Long Short-Term Memory …

Energy-Aware Real-Time Scheduling On Heterogeneous And Homogeneous Platforms In The Era Of Parallel Computing, Ashik Ahmed Bhuiyan

Electronic Theses and Dissertations, 2020-2023

Multi-core processors increasingly appear as an enabling platform for embedded systems, e.g., mobile phones, tablets, computerized numerical controls, etc. The parallel task model, where a task can execute on multiple cores simultaneously, can efficiently exploit the multi-core platform's computational ability. Many computation-intensive systems (e.g., self-driving cars) that demand stringent timing requirements often evolve in the form of parallel tasks. Several real-time embedded system applications demand predictable timing behavior and satisfy other system constraints, such as energy consumption. Motivated by the facts mentioned above, this thesis studies the approach to integrating the dynamic voltage and frequency scaling (DVFS) policy with real-time …

Robust Acceleration Of Data-Centric Applications Using Resistive Computing Systems, Baogang Zhang

Electronic Theses and Dissertations, 2020-2023

With the accessible data reaching zettabyte level, CMOS technology is reaching its limit for the data hungry applications. Moore's law has been reaching its depletion in recent studies. On the other hand, von Neumann architecture is approaching the bottleneck due to the data movement between the computing and memory units. With data movement and power budgets becoming the limiting factors of today's computing systems, in-memory computing using emerging non-volatile resistive devices has attracted an increasing amount of attention. A non-volatile resistive device may be realized using memristor, resistive random access memory (ReRAM), phase change memory (PCM), or spin-transfer torque magnetic …

Energy-Efficient In-Memory Architectures Leveraging Intrinsic Behaviors Of Embedded Mram Devices, Shadi Sheikhfaal

Electronic Theses and Dissertations, 2020-2023

For decades, innovations to surmount the processor versus memory gap and move beyond conventional von Neumann architectures continue to be sought and explored. Recent machine learning models still expend orders of magnitude more time and energy to access data in memory in addition to merely performing the computation itself. This phenomenon referred to as a memory-wall bottleneck, is addressed herein via a completely fresh perspective on logic and memory technology design. The specific solutions developed in this dissertation focus on utilizing intrinsic switching behaviors of embedded MRAM devices to design cross-layer and energy-efficient Compute-in-Memory (CiM) architectures, accelerate the computationally-intensive operations …

Optimizing Peer Selection Among Internet Service Providers (Isps), Shahzeb Mustafa

Electronic Theses and Dissertations, 2020-2023

Connections among Internet Service Providers (ISPs) form the backbone of the Internet. This enables communications across the globe. ISPs are represented as Autonomous Systems (ASes) in the global Internet and inter-ISP traffic exchange takes place via inter-AS links, which are formed based on inter-ISP connections and agreements. In addition to customer-provider agreements, a crucial type of inter-ISP agreement is peering. ISP administrators use various platforms like AP-NIC and NANOG networking events for establishing new peering connections in accordance with their business and technical needs. Such methods are often inefficient and slow, potentially resulting in missed opportunities or sub-optimal routes. The …

Research Experience For Undergraduates During Covid-19, Mustafa Akbas

Florida Statewide Symposium: Best Practices in Undergraduate Research

This presentation provides the student team interaction and mentorship experience at Embry-Riddle Aeronautical University’s “National Science Foundation (NSF) Research Experiences for Undergraduates (REU) Site: Cybersecurity Research of Unmanned Aerial Vehicles” from the summer semester of 2020. The Site had been planned for a face-of-face research experience under several mentors for an eight-week period. However, due to Covid-19, the teams had to meet, discuss, present and work online, which was both a challenge and an opportunity. Both students and mentors had lessons from this online experience that they will remember and use in the upcoming years. In this presentation, we present …

Research Review On Mixed-Criticality Scheduling, Hattan Althebeiti

Recent Advances in Real-Time Systems

No abstract provided.

Non Infinite Stories: How Digital Allow To Create Infinite Reconformations Of A Text?, David Núñez

Electronic Literature Organization Conference 2020

Last year I presented at ELO, in Ireland, the Artistic piece "Bastard" a digital fiction that combine a fragmented novel to create 10x149 differents texts and optimized in 4 billions coherent stories with narrative structures. In Orlando we want to explain how the system works, theory and functioning, and invited all the members to produce they personal "infinite" fiction.

Non Infinite Stories is an electronic publishing house that creates a dynamic hyperliterature system to give each reader a unique book by using a digital combinatorial processes, specific narrative rules and optimization of fragmented works in chapters of short narrative blocks, …

Human-Machine Communication: Complete Volume. Volume 1

Human-Machine Communication

This is the complete volume of HMC Volume 1.

Sharing Stress With A Robot: What Would A Robot Say?, Honson Y. Ling, Elin A. Björling

Human-Machine Communication

With the prevalence of mental health problems today, designing human-robot interaction for mental health intervention is not only possible, but critical. The current experiment examined how three types of robot disclosure (emotional, technical, and by-proxy) affect robot perception and human disclosure behavior during a stress-sharing activity. Emotional robot disclosure resulted in the lowest robot perceived safety. Post-hoc analysis revealed that increased perceived stress predicted reduced human disclosure, user satisfaction, robot likability, and future robot use. Negative attitudes toward robots also predicted reduced intention for future robot use. This work informs on the possible design of robot disclosure, as well as …

The Robot Privacy Paradox: Understanding How Privacy Concerns Shape Intentions To Use Social Robots, Christoph Lutz, Aurelia Tamò-Larrieux

Human-Machine Communication

Conceptual research on robots and privacy has increased but we lack empirical evidence about the prevalence, antecedents, and outcomes of different privacy concerns about social robots. To fill this gap, we present a survey, testing a variety of antecedents from trust, technology adoption, and robotics scholarship. Respondents are most concerned about data protection on the manufacturer side, followed by social privacy concerns and physical concerns. Using structural equation modeling, we find a privacy paradox, where the perceived benefits of social robots override privacy concerns.

Building A Stronger Casa: Extending The Computers Are Social Actors Paradigm, Andrew Gambino, Jesse Fox, Rabindra A. Ratan

Human-Machine Communication

The computers are social actors framework (CASA), derived from the media equation, explains how people communicate with media and machines demonstrating social potential. Many studies have challenged CASA, yet it has not been revised. We argue that CASA needs to be expanded because people have changed, technologies have changed, and the way people interact with technologies has changed. We discuss the implications of these changes and propose an extension of CASA. Whereas CASA suggests humans mindlessly apply human-human social scripts to interactions with media agents, we argue that humans may develop and apply human-media social scripts to these interactions. Our …

Me And My Robot Smiled At One Another: The Process Of Socially Enacted Communicative Affordance In Human-Machine Communication, Carmina Rodríguez-Hidalgo

Human-Machine Communication

The term affordance has been inconsistently applied both in robotics and communication. While the robotics perspective is mostly object-based, the communication science view is commonly user-based. In an attempt to bring the two perspectives together, this theoretical paper argues that social robots present new social communicative affordances emerging from a two-way relational process. I first explicate conceptual approaches of affordance in robotics and communication. Second, a model of enacted communicative affordance in the context of Human-Machine Communication (HMC) is presented. Third and last, I explain how a pivotal social robot characteristic—embodiment—plays a key role in the process of social communicative …

Ontological Boundaries Between Humans And Computers And The Implications For Human-Machine Communication, Andrea L. Guzman

Human-Machine Communication

In human-machine communication, people interact with a communication partner that is of a different ontological nature from themselves. This study examines how people conceptualize ontological differences between humans and computers and the implications of these differences for human-machine communication. Findings based on data from qualitative interviews with 73 U.S. adults regarding disembodied artificial intelligence (AI) technologies (voice-based AI assistants, automated-writing software) show that people differentiate between humans and computers based on origin of being, degree of autonomy, status as tool/tool-user, level of intelligence, emotional capabilities, and inherent flaws. In addition, these ontological boundaries are becoming increasingly blurred as technologies emulate …

Toward An Agent-Agnostic Transmission Model: Synthesizing Anthropocentric And Technocentric Paradigms In Communication, Jaime Banks, Maartje M. A. De Graaf

Human-Machine Communication

Technological and social evolutions have prompted operational, phenomenological, and ontological shifts in communication processes. These shifts, we argue, trigger the need to regard human and machine roles in communication processes in a more egalitarian fashion. Integrating anthropocentric and technocentric perspectives on communication, we propose an agent-agnostic framework for human-machine communication. This framework rejects exclusive assignment of communicative roles (sender, message, channel, receiver) to traditionally held agents and instead focuses on evaluating agents according to their functions as a means for considering what roles are held in communication processes. As a first step in advancing this agent-agnostic perspective, this theoretical paper …

Energy-Efficient Signal Conversion And In-Memory Computing Using Emerging Spin-Based Devices, Soheil Salehi Mobarakeh

Electronic Theses and Dissertations, 2020-2023

New approaches are sought to maximize the signal sensing and reconstruction performance of Internet-of-Things (IoT) devices while reducing their dynamic and leakage energy consumption. Recently, Compressive Sensing (CS) has been proposed as a technique aimed at reducing the number of samples taken per frame to decrease energy, storage, and data transmission overheads. CS can be used to sample spectrally-sparse wide-band signals close to the information rate rather than the Nyquist rate, which can alleviate the high cost of hardware performing sampling in low-duty IoT applications. In my dissertation, I am focusing mainly on the adaptive signal acquisition and conversion circuits …

Statistical And Stochastic Learning Algorithms For Distributed And Intelligent Systems, Jiang Bian

Electronic Theses and Dissertations, 2020-2023

In the big data era, statistical and stochastic learning for distributed and intelligent systems focuses on enhancing and improving the robustness of learning models that have become pervasive and are being deployed for decision-making in real-life applications including general classification, prediction, and sparse sensing. The growing prospect of statistical learning approaches such as Linear Discriminant Analysis and distributed Learning being used (e.g., community sensing) has raised concerns around the robustness of algorithm design. Recent work on anomalies detection has shown that such Learning models can also succumb to the so-called 'edge-cases' where the real-life operational situation presents data that are …

Distributed Multi-Agent Optimization And Control With Applications In Smart Grid, Towfiq Rahman

Electronic Theses and Dissertations, 2020-2023

With recent advancements in network technologies like 5G and Internet of Things (IoT), the size and complexity of networked interconnected agents have increased rapidly. Although centralized schemes have simpler algorithm design, in practicality, it creates high computational complexity and requires high bandwidth for centralized data pooling. In this dissertation, for distributed optimization of networked multi-agent architecture, the Alternating Direction Method of Multipliers (ADMM) is investigated. In particular, a new adaptive-gain ADMM algorithm is derived in closed form and under the standard convex property to greatly speed up the convergence of ADMM-based distributed optimization. Using the Lyapunov direct approach, the proposed …

Data-Driven Nonlinear Control Designs For Constrained Systems, Roland Harvey

Electronic Theses and Dissertations, 2020-2023

Systems with nonlinear dynamics are theoretically constrained to the realm of nonlinear analysis and design, while explicit constraints are expressed as equalities or inequalities of state, input, and output vectors of differential equations. Few control designs exist for systems with such explicit constraints, and no generalized solution has been provided. This dissertation presents general techniques to design stabilizing controls for a specific class of nonlinear systems with constraints on input and output, and verifies that such designs are straightforward to implement in selected applications. Additionally, a closed-form technique for an open-loop problem with unsolvable dynamic equations is developed. Typical optimal …

Enabling Recovery Of Secure Non-Volatile Memories, Mao Ye

Electronic Theses and Dissertations, 2020-2023

Emerging non-volatile memories (NVMs), such as phase change memory (PCM), spin-transfer torque RAM (STT-RAM) and resistive RAM (ReRAM), have dual memory-storage characteristics and, therefore, are strong candidates to replace or augment current DRAM and secondary storage devices. The newly released Intel 3D XPoint persistent memory and Optane SSD series have shown promising features. However, when these new devices are exposed to events such as power loss, many issues arise when data recovery is expected. In this dissertation, I devised multiple schemes to enable secure data recovery for emerging NVM technologies when memory encryption is used. With the data-remanence feature of …

Improving Usability Of Genetic Algorithms Through Self Adaptation On Static And Dynamic Environments, Reamonn Norat

Electronic Theses and Dissertations, 2020-2023

We propose a self-adaptive genetic algorithm, called SAGA, for the purposes of improving the usability of genetic algorithms on both static and dynamic problems. Self-adaption can improve usability by automating some of the parameter tuning for the algorithm, a difficult and time-consuming process on canonical genetic algorithms. Reducing or simplifying the need for parameter tuning will help towards making genetic algorithms a more attractive tool for those who are not experts in the field of evolutionary algorithms, allowing more people to take advantage of the problem solving capabilities of a genetic algorithm on real-world problems. We test SAGA and analyze …

Mfpa: Mixed-Signal Field Programmable Array For Energy-Aware Compressive Signal Processing, Adrian Tatulian

Electronic Theses and Dissertations, 2020-2023

Compressive Sensing (CS) is a signal processing technique which reduces the number of samples taken per frame to decrease energy, storage, and data transmission overheads, as well as reducing time taken for data acquisition in time-critical applications. The tradeoff in such an approach is increased complexity of signal reconstruction. While several algorithms have been developed for CS signal reconstruction, hardware implementation of these algorithms is still an area of active research. Prior work has sought to utilize parallelism available in reconstruction algorithms to minimize hardware overheads; however, such approaches are limited by the underlying limitations in CMOS technology. Herein, the …