Computer Engineering Commons^™

Evaluating The Performance Of Using Speaker Diarization For Speech Separation Of In-Person Role-Play Dialogues, Raveendra Medaramitta

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Development of professional communication skills, such as motivational interviewing, often requires experiential learning through expert instructor-guided role-plays between the trainee and a standard patient/actor. Due to the growing demand for such skills in practices, e.g., for health care providers in the management of mental health challenges, chronic conditions, substance misuse disorders, etc., there is an urgent need to improve the efficacy and scalability of such role-play based experiential learning, which are often bottlenecked by the time-consuming performance assessment process. WSU is developing ReadMI (Real-time Assessment of Dialogue in Motivational Interviewing) to address this challenge, a mobile AI solution aiming to …

Goal Management In Multi-Agent Systems, Venkatsampath Raja Gogineni

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Autonomous agents in a multi-agent system coordinate to achieve their goals. However, in a partially observable world, current multi-agent systems are often less effective in achieving their goals. In much part, this limitation is due to an agent's lack of reasoning about other agents and their mental states. Another factor is the agent's inability to share required knowledge with other agents and the lack of explanations in justifying the reasons behind the goal. This research addresses these problems by presenting a general approach for agent goal management in unexpected situations. In this approach, an agent applies three main concepts: goal …

Texture-Driven Image Clustering In Laser Powder Bed Fusion, Alexander H. Groeger

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The additive manufacturing (AM) field is striving to identify anomalies in laser powder bed fusion (LPBF) using multi-sensor in-process monitoring paired with machine learning (ML). In-process monitoring can reveal the presence of anomalies but creating a ML classifier requires labeled data. The present work approaches this problem by printing hundreds of Inconel-718 coupons with different processing parameters to capture a wide range of process monitoring imagery with multiple sensor types. Afterwards, the process monitoring images are encoded into feature vectors and clustered to isolate groups in each sensor modality. Four texture representations were learned by training two convolutional neural network …

Texture-Driven Image Clustering In Laser Powder Bed Fusion, Alexander H. Groeger

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The additive manufacturing (AM) field is striving to identify anomalies in laser powder bed fusion (LPBF) using multi-sensor in-process monitoring paired with machine learning (ML). In-process monitoring can reveal the presence of anomalies but creating a ML classifier requires labeled data. The present work approaches this problem by printing hundreds of Inconel-718 coupons with different processing parameters to capture a wide range of process monitoring imagery with multiple sensor types. Afterwards, the process monitoring images are encoded into feature vectors and clustered to isolate groups in each sensor modality. Four texture representations were learned by training two convolutional neural network …

Evaluating The Performance Of Using Speaker Diarization For Speech Separation Of In-Person Role-Play Dialogues, Raveendra Medaramitta

Browse all Theses and Dissertations

Development of professional communication skills, such as motivational interviewing, often requires experiential learning through expert instructor-guided role-plays between the trainee and a standard patient/actor. Due to the growing demand for such skills in practices, e.g., for health care providers in the management of mental health challenges, chronic conditions, substance misuse disorders, etc., there is an urgent need to improve the efficacy and scalability of such role-play based experiential learning, which are often bottlenecked by the time-consuming performance assessment process. WSU is developing ReadMI (Real-time Assessment of Dialogue in Motivational Interviewing) to address this challenge, a mobile AI solution aiming to …

Mathematical Formula Recognition And Automatic Detection And Translation Of Algorithmic Components Into Stochastic Petri Nets In Scientific Documents, Elisavet Elli Kostalia

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A great percentage of documents in scientific and engineering disciplines include mathematical formulas and/or algorithms. Exploring the mathematical formulas in the technical documents, we focused on the mathematical operations associations, their syntactical correctness, and the association of these components into attributed graphs and Stochastic Petri Nets (SPN). We also introduce a formal language to generate mathematical formulas and evaluate their syntactical correctness. The main contribution of this work focuses on the automatic segmentation of mathematical documents for the parsing and analysis of detected algorithmic components. To achieve this, we present a synergy of methods, such as string parsing according to …

Goal Management In Multi-Agent Systems, Venkatsampath Raja Gogineni

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Autonomous agents in a multi-agent system coordinate to achieve their goals. However, in a partially observable world, current multi-agent systems are often less effective in achieving their goals. In much part, this limitation is due to an agent's lack of reasoning about other agents and their mental states. Another factor is the agent's inability to share required knowledge with other agents and the lack of explanations in justifying the reasons behind the goal. This research addresses these problems by presenting a general approach for agent goal management in unexpected situations. In this approach, an agent applies three main concepts: goal …

Detecting Server-Side Web Applications With Unrestricted File Upload Vulnerabilities, Jin Huang

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Vulnerable web applications fundamentally undermine website security as they often expose critical infrastructures and sensitive information behind them to potential risks and threats. Web applications with unrestricted file upload vulnerabilities allow attackers to upload a file with malicious code, which can be later executed on the server by attackers to enable various attacks such as information exfiltration, spamming, phishing, and spreading malware. This dissertation presents our research in building two novel frameworks to detect server-side applications vulnerable to unrestricted file uploading attacks. We design the innovative model that holistically characterizes both data and control flows using a graphbased data structure. …

A Deep Learning Approach To Lncrna Subcellular Localization Using Inexact Q-Mer, Weijun Yi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Long non coding Ribonucleic Acids (lncRNAs) can be localized to different cellular components, such as the nucleus, exosome, cytoplasm, ribosome, etc. Their biological functions can be influenced by the region of the cell they are located. Many of these lncRNAs are associated with different challenging diseases. Thus, it is crucial to study their subcellular localization. However, compared to the vast number of lncRNAs, only relatively few have annotations in terms of their subcellular localization. Conventional computational methods use q-mer profiles from lncRNA sequences and then train machine learning models, such as support vector machines and logistic regression with the profiles. …

Mitigating Insider Threats In A Cooperative Adaptive Cruise Control System Using Local Intra-Vehicle Data, Alexander Francis Colon

Graduate Theses, Dissertations, and Problem Reports (ETD)

With the rise of Connected-and-Automated-Vehicle (CAV) technologies on roadways, transportation networks have become increasingly connected through Vehicle-to-Everything (V2X) systems. With access to the additional data from V2X, modern cruise control systems like Adaptive Cruise Control (ACC) are further improved upon to develop systems like Cooperative ACC (CACC) which reduces traffic congestion and increases driver safety and energy efficiency. With that increased connectivity, previously closed vehicle systems are now vulnerable to new security threats which pose new technical challenges. Significant research has been done to strengthen the network against external threats such as denial-of-service attacks (DoS) or passive eavesdropping attacks using …

Planning Algorithms Under Uncertainty For A Team Of A Uav And A Ugv For Underground Exploration, Matteo De Petrillo

Graduate Theses, Dissertations, and Problem Reports (ETD)

Robots’ autonomy has been studied for decades in different environments, but only recently, thanks to the advance in technology and interests, robots for underground exploration gained more attention. Due to the many challenges that any robot must face in such harsh environments, this remains an challenging and complex problem to solve.

As technology became cheaper and more accessible, the use of robots for underground ex- ploration increased. One of the main challenges is concerned with robot localization, which is not easily provided by any Global Navigation Services System (GNSS). Many developments have been achieved for indoor mobile ground robots, making …

Using Distributed Ledger Technologies In Vanets To Achieve Trusted Intelligent Transportation Systems, Fares Nabil Elamine

Graduate Theses, Dissertations, and Problem Reports (ETD)

With the recent advancements in the networking realm of computers as well as achieving real-time communication between devices over the Internet, IoT (Internet of Things) devices have been on the rise; collecting, sharing, and exchanging data with other connected devices or databases online, enabling all sorts of communications and operations without the need for human intervention, oversight, or control. This has caused more computer-based systems to get integrated into the physical world, inching us closer towards developing smart cities.

The automotive industry, alongside other software developers and technology companies have been at the forefront of this advancement towards achieving smart …

Increasing The Reliability Of Software Systems On Small Satellites Using Software-Based Simulation Of The Embedded System, Matthew D. Grubb

Graduate Theses, Dissertations, and Problem Reports (ETD)

The utility of Small Satellites (SmallSats) for technology demonstrations and scientific research has been proven over the past few decades by governments, universities, and private companies. While the research and technology demonstration objectives that can be provided by these SmallSats are becoming similar to larger spacecraft, their reliability still falls behind. This is in part due to the reduced cost of SmallSat missions in comparison to large spacecraft, which requires cheaper components, rapid development schedules, and accepted risk. In these missions, the importance of the flight software is often overlooked, and the software is rushed through development and not fully …

Touching Light: A Framework For The Facilitation Of Music-Making In Mixed Reality, Ian Thomas Riley

Graduate Theses, Dissertations, and Problem Reports (ETD)

Drawing upon the historical development of analog and digital technologies alongside the proliferation of computer-assisted performance practices, this research seeks to develop a framework for integrating Mixed Reality applications to live musical performance, specifically through the creation of a Microsoft HoloLens 2 Mixed Reality application in order to facilitate a live performance of an original musical composition for percussion and real-time Mixed Reality environment. Mixed Reality enables a performer to interact with virtual (holograms, VSTs, etc.) and physical (vibraphone, tuned drums, microphones, etc.) objects simultaneously. Tandem to the development of the conceptual framework was the composition of an original score …

Deep Learning Architectures For Heterogeneous Face Recognition, Seyed Mehdi Iranmanesh

Graduate Theses, Dissertations, and Problem Reports (ETD)

Face recognition has been one of the most challenging areas of research in biometrics and computer vision. Many face recognition algorithms are designed to address illumination and pose problems for visible face images. In recent years, there has been significant amount of research in Heterogeneous Face Recognition (HFR). The large modality gap between faces captured in different spectrum as well as lack of training data makes heterogeneous face recognition (HFR) quite a challenging problem. In this work, we present different deep learning frameworks to address the problem of matching non-visible face photos against a gallery of visible faces.

Algorithms for …

Energy Harvesting And Sensor Based Hardware Security Primitives For Cyber-Physical Systems, Carson Labrado

Theses and Dissertations--Electrical and Computer Engineering

The last few decades have seen a large proliferation in the prevalence of cyber-physical systems. Although cyber-physical systems can offer numerous advantages to society, their large scale adoption does not come without risks. Internet of Things (IoT) devices can be considered a significant component within cyber-physical systems. They can provide network communication in addition to controlling the various sensors and actuators that exist within the larger cyber-physical system. The adoption of IoT features can also provide attackers with new potential avenues to access and exploit a system's vulnerabilities. Previously, existing systems could more or less be considered a closed system …

Toward Intelligent Welding By Building Its Digital Twin, Qiyue Wang

Theses and Dissertations--Electrical and Computer Engineering

To meet the increasing requirements for production on individualization, efficiency and quality, traditional manufacturing processes are evolving to smart manufacturing with the support from the information technology advancements including cyber-physical systems (CPS), Internet of Things (IoT), big industrial data, and artificial intelligence (AI). The pre-requirement for integrating with these advanced information technologies is to digitalize manufacturing processes such that they can be analyzed, controlled, and interacted with other digitalized components. Digital twin is developed as a general framework to do that by building the digital replicas for the physical entities. This work takes welding manufacturing as the case study to …

Designing Novel Hardware Security Primitives For Smart Computing Devices, Amitkumar Degada

Theses and Dissertations--Electrical and Computer Engineering

Smart computing devices are miniaturized electronics devices that can sense their surroundings, communicate, and share information autonomously with other devices to work cohesively. Smart devices have played a major role in improving quality of the life and boosting the global economy. They are ubiquitously present, smart home, smart city, smart girds, industry, healthcare, controlling the hazardous environment, and military, etc. However, we have witnessed an exponential rise in potential threat vectors and physical attacks in recent years. The conventional software-based security approaches are not suitable in the smart computing device, therefore, hardware-enabled security solutions have emerged as an attractive choice. …

The Design, Development And Validation Of A Persuasive Content Generator, Sam Khataei, Michael J. Hine, Ali Arya

Journal of International Technology and Information Management

This paper addresses the automatic generation of persuasive content to influence users’ attitude and behaviour. Our research extends current approaches by leveraging individuals’ social media profiles and activity to personalize the persuasive content. Unlike most other implemented persuasive technology, our system is generic and can be adapted to any domain where collections of electronic text are available. Using the Yale Attitude Change approach, we describe: the multi-layered Pyramid of Individualization model; the design, development, and validation of integrated software that can generate individualized persuasive content based on a user’s social media profile and activity. Results indicate the proposed system can …

Wireless Mobile Phone Technology, Deregulation Policy, Competition And Economic Welfare In Nigeria’S Telecom Industry: An Analytic Model, Onochie J. Dieli Phd

Journal of International Technology and Information Management

This analytic model is about the Nigerian telecom industry’s structural change caused by the arrival of a new wireless mobile phone technology. Nigeria’s telecom industry transformed from natural monopoly to competitive market as a result of deregulation that occurred in 1999. Under the price regulation using underground or above the ground cable telephone lines, it could run only with the help of government subsidies. This study argues that the arrival of a new telecomm technology was the key to success of Nigeria’s deregulation of its telecom industry. An analysis of a simple microeconomic model shows that with the new wireless …