Computer Engineering Commons^™

Designs And Practical Control Methods For Soft Parallel Robots, Benjamin T. Buzzo

Graduate Theses, Dissertations, and Problem Reports (ETD)

The use of soft robotics is becoming an increasingly researched topic, since they can provide more flexibility in movements and increase safety when working with humans. However, they are more susceptible to modeling and manufacturing errors in the design.

The objective of this thesis is two-fold, the first objective is to determine the benefits and limitations of using calibration tables that rely on the PWM signals instead of modeling as a control method. If calibration tables are not adequate to achieve a high level of precision. The second objective is to determine if using a tethered mobile robot in unison …

Evaluating Social Media As A Medium Of Private Communication Through Steganographic Images, Kendall Weldon Coles

Graduate Theses, Dissertations, and Problem Reports (ETD)

Social media is a vastly used communication tool with billions of users worldwide. These social networks provide users the ability to share their ideas and thoughts through the messages, videos, and images that they post. The images that are shared can possibly be embedded with private messages through the use of a steganographic tool. The messages are embedded in a fashion that doesn’t change the visual appearance of an image. This allows for these types of images to hide in plain sight, which creates the possibility of someone communicating privately in a public social media setting. This project proved how …

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 …

Active Localization For Robotic Systems: Algorithms And Cost Metrics, Jared Strader

Graduate Theses, Dissertations, and Problem Reports (ETD)

In the real world, a robotic system must operate in the presence of motion and sensing uncertainty. This is caused by the fact that the motion of a robotic system is stochastic due to disturbances from the environment, and the states are only partially observable due noise in the sensor measurements. As a result, the true state of a robotic system is unknown, and estimation techniques must be used to infer the states from the belief, which is the probability distribution over all possible states. Accordingly, a robotic system must be capable of reasoning about the quality of the belief …

Rania: A Framework For A Modular, Voice Enabled, Gerontechnology-Centric, Smart-Home System, Emily Francis

Graduate Theses, Dissertations, and Problem Reports (ETD)

In the United States, the proportion of senior citizens is expected to rise significantly over the next few decades. This increasing number of senior citizens combined with the increasing demand for at home healthcare workers is putting a strain on the elderly healthcare system. Smart-home healthcare technology { such as smart medication dispensers, fall detection systems, smart pantry systems, etc. { has the potential to alleviate this strain on the elderly healthcare system. Smart devices can give an individual more autonomized and personalized surveillance of their health and well-being. While these devices are beneficial as standalone devices, they would be …

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. …

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 …

Deep Learning Methods For Fingerprint-Based Indoor And Outdoor Positioning, Fahad Alhomayani

Electronic Theses and Dissertations

Outdoor positioning systems based on the Global Navigation Satellite System have several shortcomings that have deemed their use for indoor positioning impractical. Location fingerprinting, which utilizes machine learning, has emerged as a viable method and solution for indoor positioning due to its simple concept and accurate performance. In the past, shallow learning algorithms were traditionally used in location fingerprinting. Recently, the research community started utilizing deep learning methods for fingerprinting after witnessing the great success and superiority these methods have over traditional/shallow machine learning algorithms. The contribution of this dissertation is fourfold:

First, a Convolutional Neural Network (CNN)-based method for …

Design Of Lower Legs Of Mithra, A High-Performance Backdrivable Humanoid Robot, Drake Taylor

Electronic Theses and Dissertations

This thesis presents the design of the knee and ankle of Mithra, a new humanoid robot that aims to be an energy-efficient and highly agile machine. Mithra makes use of new optimization metrics for legged robots to develop a system capable of mimicking human movement. A series of low-impedance, high-torque actuator systems were developed with the goal of creating lightweight, powerful, and robust motion. The structure of Mithra's legs mimics the human structure in leg segment length and weight proportions. Detailed design and analysis were conducted in order to allow Mithra to be a robust and maintainable system. Mithra will …

Blockchain-Based Architecture For Secured Cyberattack Signatures And Features Distribution, Oluwaseyi J. Ajayi

Dissertations and Theses

One effective way of detecting malicious traffic in computer networks is intrusion detection systems (IDS). Despite the increased accuracy of IDSs, distributed or coordinated attacks can still go undetected because of the single vantage point of the IDSs. Due to this reason, there is a need for attack characteristics' exchange among different IDS nodes. Another reason for IDS coordination is that a zero-day attack (an attack without a known signature) experienced in organizations located in different regions is not the same. Collaborative efforts of the participating IDS nodes can stop more attack threats if IDS nodes exchange these attack characteristics …

A Meta-Gradient Approach To Learning Cooperative Multi-Agent Communication Topology, Qi Zhang, Dingyang Chen

Publications

In cooperative multi-agent reinforcement learning (MARL), agents often can only partially observe the environment state, and thus communication is crucial to achieving coordination. Communicating agents must simultaneously learn to whom to communicate (i.e., communication topology) and how to interpret the received message for decision-making. Although agents can efficiently learn communication interpretation by end-to-end backpropagation, learning communication topology is much trickier since the binary decisions of whether to communicate impede end-to-end differentiation. As evidenced in our experiments, existing solutions, such as reparameterization tricks and reformulating topology learning as reinforcement learning, often fall short. This paper introduces a meta-learning framework that aims …

Parallel Computation, Mahesh Wosti

Student Academic Conference

Parallel computing has always fascinated me since I became aware of it. I think it is the only path forward if we are to build and make a super-fast computer in days to come. For my senior seminar, I want to build a simple framework of the parallel system and dig deeper into potential benefits and drawbacks of using a parallel system compared to the serial computing that is still pervasive in today’s modern technology.

Intrusion Detection For Industrial Control Systems, Kurt Lamon

EWU Masters Thesis Collection

Industrial Control Systems (ICS) are rapidly shifting from closed local networks, to remotely accessible networks. This shift has created a need for strong cybersecurity anomaly and intrusion detection for these systems; however, due to the complexity and diversity of ICSs, well defined and reliable anomaly and intrusion detection systems are still being developed. Machine learning approaches for anomaly and intrusion detection on the network level may provide general protection that can be applied to any ICS. This paper explores two machine learning applications for classifying the attack label of the UNSW-NB15 dataset. The UNSW-NB15 is a benchmark dataset that was …

Arkhe - Unmanned Detection Robot, Hannah Klooster

Senior Honors Theses and Projects

Our project is an Unmanned Thermal Detection Robot. Our robot contains a visual camera, a sonar sensor, and a thermal sensor. This project involves hardware building and coding of the sensors and robot itself. The purpose of this project is to create an accessible and affordable unmanned robot with sensors capable of being able to detect human life forms in disaster areas, or areas inaccessible to humans, and to protect the lives of rescuers, find people in disaster areas quicker, and to help save lives. Our project has successfully created an affordable robot that uses sensors to detect and avoid …

Instrumentation, Modeling, And Sound Metamodeling Foundations For Complex Hybrid Systems, Natasha Amelia Jarus

Doctoral Dissertations

Many of our critical infrastructures, from power grids to water distribution networks, are complex hybrid systems that use software to control their non-trivial physical dynamics. These systems must be able to capably serve their purpose, while also being reliable, dependable, safe, secure, and efficient. Representation and analysis of these features requires the creation of several distinct models. These models may encode design goals or be derived from collected instrumentation data, reflecting both how a system ought to operate and how it does operate. It is essential to ensure that all of these models consistently and accurately describe the same system. …

Topological Biclustering Artmap, Raghu Yelugam

Masters Theses

”Detection of gene mutations is central for assessing genetic factors affecting disease predisposition, genetic causes of a particular disease, and gene-targeted treatment. DNA microarray methods are widely used to detect mutations by contrasting the expression levels of thousands of genes together under varying experimental conditions. The experimental conditions could be diseased cell states compared with the normal cell states. Biclustering, a robust exploratory data analysis tool, can be applied to microarray data to detect subsets of genes that co-express highly only for a subset of experimental conditions. Such detection is crucial for gaining insights into gene regulatory networks, differential gene …

Neural Network Supervised And Reinforcement Learning For Neurological, Diagnostic, And Modeling Problems, Donald Wunsch Iii

Masters Theses

“As the medical world becomes increasingly intertwined with the tech sphere, machine learning on medical datasets and mathematical models becomes an attractive application. This research looks at the predictive capabilities of neural networks and other machine learning algorithms, and assesses the validity of several feature selection strategies to reduce the negative effects of high dataset dimensionality. Our results indicate that several feature selection methods can maintain high validation and test accuracy on classification tasks, with neural networks performing best, for both single class and multi-class classification applications. This research also evaluates a proof-of-concept application of a deep-Q-learning network (DQN) to …

การประยุกต์การวิเคราะห์เครือข่ายสังคมเพื่อปรับปรุงกระบวนการทดสอบซอฟต์แวร์, พรรณธิภา บุญมาพบ

Chulalongkorn University Theses and Dissertations (Chula ETD)

Jira Software เป็นโซลูชันการจัดการโครงการแบบอไจล์ ซึ่งเดิมออกแบบมาให้เป็นเครื่องมือในการติดตามข้อบกพร่องและปัญหาที่เกิดขึ้นภายในโครงการ การค้นหาปัญหาหรือข้อมูลข้อบกพร่องสามารถทำได้โดยใช้ Jira Query Language (JQL) อย่างไรก็ตาม การสืบค้นปัญหาหรือข้อบกพร่องจากแหล่งที่เก็บข้อมูลจะคืนค่าข้อมูลที่เฉพาะเจาะจงมาอย่างง่ายและธรรมดาทั่วไป ในงานวิจัยนี้ ได้นำเสนอแนวทางการสร้างภาพข้อมูลเครือข่ายเพื่อเปิดเผยความสัมพันธ์และการสื่อสารระหว่างตัวบทบาท เช่น คุณสมบัติของซอฟต์แวร์ ข้อบกพร่อง และบุคลากร โดยเทคนิคการวิเคราะห์เครือข่ายโซเชียลใช้สำหรับวิเคราะห์ข้อบกพร่องที่รวบรวมจากโครงการซอฟต์แวร์ภายในธนาคาร และ Gephi ถูกใช้เป็นเครื่องมือในการสร้างเครือข่ายของบทบาทที่ระบุเป็นโหนดและการเชื่อมโยงของโหนดเหล่านั้น ซึ่งแนวทางของการวิเคราะห์เครือข่ายภาพนั้นใช้ได้จริงและให้ข้อมูลเชิงลึกในการวิเคราะห์ข้อบกพร่องที่จำเป็นสำหรับกระบวนการพัฒนาซอฟต์แวร์ในเชิงรุก

Transforming Timing Diagram Into Timed Automata For Preemptive Scheduling, อมรัตน์ พิมโคตร

Chulalongkorn University Theses and Dissertations (Chula ETD)

งานที่เกิดขึ้นพร้อมกันในระบบเรียลไทม์อาจต้องการทรัพยากรที่ใช้ร่วมกันอย่างจำกัด เช่นการใช้งานร่วมกันของ CPU เพียงตัวเดียวที่มีงานเป็นจำนวนมาก เมื่อใช้การจัดกระบวนการเชิงพรีเอ็มทีฟ ซึ่งงานที่กำลังทำงานอยู่ที่มีค่าลำดับความสำคัญต่ำกว่ามักจะถูกจัดลำดับให้อยู่ในสถานะพักการทำงานหรือสถานะโดเมน โดยงานใหม่ที่มีค่าลำดับความสำคัญสูงกว่าจะเข้ามาแทนที่ สุดท้ายจึงกลายเป็นว่างานใหม่เข้ามาทำงานแทนลำดับงานที่โดนแทรกหรือถูกพรีเอ็มทีฟไว้ก่อนหน้านี้ที่มีค่าลำดับความสำคัญต่ำกว่า งานที่มีค่าลำดับความสำคัญต่ำกว่าดังกล่าวจะเริ่มต้นทำงานอีกครั้งเพื่อดำเนินการต่อในสถานะที่ทำงานทันทีหลังจากงานที่มีค่าลำดับความสำคัญสูงกว่าได้ทำงานเสร็จสิ้น แผนภาพเวลาเป็นแผนภาพที่มีลักษณะงานเป็นอิสระต่อกัน และงานจะถูกเริ่มต้นพร้อมกัน ผลกระทบของการจัดกระบวนการเชิงพรีเอ็มทีฟเอาไว้จะมีความสัมพันธ์กันและทำให้การดำเนินของเส้นเวลาหรือไทม์ไลน์ของงานที่เกิดขึ้นพร้อมกันเหล่านี้ถูกเปลี่ยนแปลงไป กฎการจับคู่สำหรับการแปลงแผนภาพเวลาที่เป็นอิสระต่อกันเป็นไทมด์ออโตมาตาที่ได้รับการออกแบบในวิทยานิพนธ์นี้ และยังมีเครื่องมือซอฟต์แวร์ที่ได้รับการพัฒนาเพื่อแปลงไฟล์ต้นทางนำเข้าสกุลไฟล์ XML ของแผนภาพเวลาเป็นไฟล์ไทมด์ออโตมาตา สามารถจำลองแผนภาพไทมด์ออโตมาตาด้วยเครื่องมือ UPPAAL ซึ่งผลลัพธ์ของไทมด์ออโตมาตาจะแสดงกรอบเวลาโดยรวมของงานที่เกิดขึ้นพร้อมกันอันเป็นผลกระทบของการจัดกำหนดการเชิงฟรีเอ็มทีฟ การจำลองไทมด์ออโตมาตาจะจัดเตรียมตัวแปรนาฬิกาและสถานะโดเมนพิเศษเพิ่มเติม จากนั้นจึงนำไทมด์ออโตมาตาที่แปลงมาทวนสอบคุณสมบัติ TCTL ว่าการทำงานนั้นถูกต้อง เครื่องมือซอฟต์แวร์ของเราจะดำเนินการแปลงไดอะแกรมสำหรับการจัดกระบวนการเชิงพรีเอ็มทีฟ และใช้กรณีศึกษาสามกรณีเพื่อแสดงกระบวนการแปลงและการจำลองขั้นตอนกระบวนการทำงาน

Performance Improvement Of Cms Simulation Via Loop Transformation, Teerit Ploensin

Chulalongkorn University Theses and Dissertations (Chula ETD)

High performance processor can tackle bottleneck issues by increasing vector lengths and leveling effectiveness of memory hierarchies to address these issue. Manual optimization of code is a difficult task when having multiple architecturedependent transformation. Our goal is to develop a tool that performs source code transformation based on loop optimization techniques, since a loop plays an important role in improving of performance in scientific simulation software. We implement an source-to-source transformation tool based libTooling, a Clang’s library, based on polyhedral model to simplify a loop transformation of CMSSW building pipeline. The tool also can be used for automatically transformation. The …

Re-Designing Main Memory Subsystems With Emerging Monolithic 3d (M3d) Integration And Phase Change Memory Technologies, Chao-Hsuan Huang

Theses and Dissertations--Electrical and Computer Engineering

Over the past two decades, Dynamic Random-Access Memory (DRAM) has emerged as the dominant technology for implementing the main memory subsystems of all types of computing systems. However, inferring from several recent trends, computer architects in both the industry and academia have widely accepted that the density (memory capacity per chip area) and latency of DRAM based main memory subsystems cannot sufficiently scale in the future to meet the requirements of future data-centric workloads related to Artificial Intelligence (AI), Big Data, and Internet-of-Things (IoT). In fact, the achievable density and access latency in main memory subsystems presents a very fundamental …

Edge Processing Of Image For Uas Sense And Avoidance, Christopher J. Rave

Browse all Theses and Dissertations

Today there is a large market for Unmanned Aerial Systems. Although most current systems are remotely piloted by operators on the ground, increasingly, many of these systems will use some sort of automatic flight controller to help mitigate new challenges, due to their deployment at growing scale. These challenges include, but are not limited to, shortage of FAA-certified UAS pilots, transmission bandwidth and delay constraints and cyber security threats associated with wireless networking, profitability of operations constrained by energy capacity and efficiency and air dynamics planning, and etc. In order to address these rising challenges, this thesis is a part …

Arise - Augmented Reality In Surgery And Education, Sadan Suneesh Menon

Browse all Theses and Dissertations

Human errors in healthcare can be fatal. Proper physical assessment of patients to avoid such errors is of paramount importance. Incorrect or insufficient assessment of the patient can cause treatment delays that may lead to negative outcomes. In this dissertation we introduce innovative technology to assist surgeons in patient assessment as well as during the training of nurses in order to enhance learning. Technological advancements have made it possible to visualize overlays of computer-generated 3D models on real-world surfaces. This technology is called augmented reality. Using Steady State Topography (SST) brain imaging to examine the brain activity of people who …

Leveraging Sequential Nature Of Conversations For Intent Classification, Shree Gotteti

Browse all Theses and Dissertations

Conversations are more than just a sequence of text, it is where two or more participants interact in order to achieve their goals. Conversation Understanding (CU) requires all participants to understand each others intent. In the past decade, CU has been extended from automated human-human text processing to build automated conversational agents for human-machine interactions. Despite their popularity, these automated conversational agents (like Siri, Alexa, etc) can't handle more than one or two utterances, and they don't recognize conversations as intents. The development of approaches that extract intents behind an utterance is essential for the advancements of Question Answering (QA) …

Hidden Markov Model And Cyber Deception For The Prevention Of Adversarial Lateral Movement, Md Ali Reza Al Amin, Sachin Shetty, Laurent Njilla, Deepak K. Tosh, Charles Kamhoua

Computational Modeling & Simulation Engineering Faculty Publications

Advanced persistent threats (APTs) have emerged as multi-stage attacks that have targeted nation-states and their associated entities, including private and corporate sectors. Cyber deception has emerged as a defense approach to secure our cyber infrastructure from APTs. Practical deployment of cyber deception relies on defenders' ability to place decoy nodes along the APT path optimally. This paper presents a cyber deception approach focused on predicting the most likely sequence of attack paths and deploying decoy nodes along the predicted path. Our proposed approach combines reactive (graph analysis) and proactive (cyber deception technology) defense to thwart the adversaries' lateral movement. The …

Modeling And Simulation Of Cascading Failures In Transportation Systems During Hurricane Evacuations, Yuan Zhu, Kaan Ozbay, Hong Yang, Fan Zuo, Di Sha

Computational Modeling & Simulation Engineering Faculty Publications

Effective and timely evacuation is critical in alleviating the impact of hurricanes. As such, evacuation models are often sought to support the preparedness of evacuations. One important task in the modeling process is to evaluate exogenous factors that cause transportation system capacity loss during evacuation. Typical factors include direct damage to the roadway network due to storm surge and cascading impacts because of other facilities failures. For example, power outage can lead to signal failure and subway suspension. This paper aims to develop a macroscopic simulation-based approach to study the capacity loss of the roadway network in evacuation due to …

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 …

Development Of An Autonomous Navigation System For The Shuttle Car In Underground Room & Pillar Coal Mines, Vasileios Androulakis

Theses and Dissertations--Mining Engineering

In recent years, autonomous solutions in the multi-disciplinary field of the mining engineering have been an extremely popular applied research topic. The growing demand for mineral supplies combined with the steady decline in the available surface reserves has driven the mining industry to mine deeper underground deposits. These deposits are difficult to access, and the environment may be hazardous to mine personnel (e.g., increased heat, difficult ventilation conditions, etc.). Moreover, current mining methods expose the miners to numerous occupational hazards such as working in the proximity of heavy mining equipment, possible roof falls, as well as noise and dust. As …