Engineering Commons^™

Computer Security Lab Experiment, Orit D. Gruber, Herbert Schanker

Open Educational Resources

This is a basic experiment for all students of all majors to explore Computer Security. Each instruction included in this experiment is conducted online via a Web Browser; Firefox or Chrome is recommended. Software does not need to be downloaded nor installed. The step by step instructions in this experiment include interactive questions and observations which are then included in the (student's) final report.

Whispers Of Ai: Unveiling The Paradox Of Gpt Titans, Faria R. Promi, Qing Qing Zhuo

Publications and Research

The advent of large-scale language models, such as GPT, has sparked a revolution in artificial intelligence, enabling computers to comprehend and generate human-like text with remarkable ease. These models can write articles, answer questions, and even engage in conversations that mimic human speech. While their abilities are impressive, concerns about their societal impact abound. This research project dives deep into exploring the multifaceted aspects of these AI titans. We will investigate the positive aspects of big talking AI models through a thorough examination of existing literature, real-world examples, such as their potential to enhance education, entertainment, and customer service experiences. …

Multi-Perspective Analysis For Derivative Financial Product Prediction With Stacked Recurrent Neural Networks, Natural Language Processing And Large Language Model, Ethan Lo

Dissertations, Theses, and Capstone Projects

This study developed a multi-perspective, AI-powered model for predicting E-Mini S&P 500 Index Futures prices, tackling the challenging market dynamics of these derivative financial instruments. Leveraging FinBERT for analysis of Wall Street Journal data alongside technical indicators, trader positioning, and economic factors, my stacked recurrent neural network built with LSTMs and GRUs achieves significantly improved accuracy compared to single sub-models. Furthermore, ChatGPT generation of human-readable analysis reports demonstrates the feasibility of using large language models in financial analysis. This research pioneers the use of stacked RNNs and LLMs for multi-perspective financial analysis, offering a novel blueprint for automated prediction and …

Data Science And The Ethics Of Private Information, Faria R. Promi

Publications and Research

This research focuses on the moral questions linked to modern data technologies like Big Data and the Internet of Things. These technologies can be, but they are also about privacy and keeping data secure. We've looked at what experts say about these concerns and discovered that most agree we need to safeguard people's privacy and data. Our research encourages everyone to use these technologies, finding a balance between technological progress and responsible, ethical behavior. This way, we can enjoy the benefits of these technologies while also respecting individuals' privacy and data rights. The study reviews what experts have said about …

The Potential Of The Implementation Of Offline Robotic Programming Into Automation-Related Pedagogy, Max Rios Carballo, Xavier Brown

Publications and Research

In this study, the offline programming tool RoboDK is used to program industrial robots for the automation sector. The study explores the feasibility of using this non-disruptive robot programming software for classroom use; assesses how well RoboDK can be used to program various robots used in the industry; creates and tests various applications; and pinpoints technical obstacles that prevent a smooth link between offline programming and actual robots. Initial results indicate that RoboDK is an effective tool for deploying its offline programming code to a Universal Robot, UR3e. There are many potential for advanced applications. The goal of the project …

Development Of A Raspberry Pi-Controlled Vex Robot For A Robotics Technology Course, Lili Ma, Justin Bartholomew, Yu Wang, Xiaohai Li

Publications and Research

This paper describes the development of a Raspberry PI-controlled VEX robot for an undergraduate robotic course. The Raspberry PI controls the mobile base built using the VEX robotics kit without using the Cortex micro-controller that comes with the kit. The aim is to create a physical robot that is manageable, easily replicable, and capable of performing advanced robotic control tasks such as vision-based control.

The constructed robot adopts the great features of the PI and the VEX hardware. Firstly, the VEX hardware consists of various sensors and actuators for students to practice the construction and assembly of an autonomous robot. …

Introducing Ros-Projects To Undergraduate Robotic Curriculum, Lili Ma, Yu Wang, Chen Xu, Xiaohai Li

Publications and Research

This paper describes three MATLAB-ROS-based simulation projects developed for an undergraduate robotics course. The Robot Operating System (ROS) is an open-source framework that helps researchers and developers build and reuse code between robotics applications. Adoption of ROS in the undergraduate curricula is still rare due to its demanding requirements of C++/Python/Java programming skills and familiarity with Linux. Recently, MathWorks released its ROS Toolbox, making it easier to interact with simulators like the Gazebo and ROS-supported physical robots. The MATLAB-ROS-Gazebo simulation platform allows students to utilize other MATLAB Toolboxes, such as Image Processing, Computer Vision, Visualization, and Navigation Toolboxes, for fast …

Types Of Cyber Attacks And Incident Responses, Kaung Myat Thu

Publications and Research

Cyber-attacks are increasingly prevalent in today's digital age, and their impact can be severe for individuals, organizations, and governments. To effectively protect against these threats, it is essential to understand the different types of attacks and have an incident response plan in place to minimize damage and restore normal operations quickly.

This research aims to contribute to the field by addressing the following questions: What are the main types of cyber-attacks, and how can organizations effectively respond to these incidents? How can the incident response process be improved through post-incident activities?

The study examines various cyber-attack types, including malware, phishing, …

Stand-Up Comedy Visualized, Berna Yenidogan

Dissertations, Theses, and Capstone Projects

Stand-up comedy has become an increasingly popular form of comedy in the recent years and comedians reach audiences beyond the halls they are performing through streaming services, podcasts and social media. While comedic performances are typically judged by how 'funny' they are, which could be proxied by the frequency and intensity of laughs through the performance, comedians also explore untapped social issues and provoke conversation, especially in this age where interaction with artists goes beyond their act. It is easy to see commonalities in the topics addressed in comedians’ work such as relationships, race and politics.This project provides an interactive …

Resource Management In Mobile Edge Computing For Compute-Intensive Application, Xiaojie Zhang

Dissertations, Theses, and Capstone Projects

With current and future mobile applications (e.g., healthcare, connected vehicles, and smart grids) becoming increasingly compute-intensive for many mission-critical use cases, the energy and computing capacities of embedded mobile devices are proving to be insufficient to handle all in-device computation. To address the energy and computing shortages of mobile devices, mobile edge computing (MEC) has emerged as a major distributed computing paradigm. Compared to traditional cloud-based computing, MEC integrates network control, distributed computing, and storage to customizable, fast, reliable, and secure edge services that are closer to the user and data sites. However, the diversity of applications and a variety …

Deception Detection Across Domains, Languages And Modalities, Subhadarshi Panda

Dissertations, Theses, and Capstone Projects

With the increase of deception and misinformation especially in social media, it has become crucial to develop machine learning methods to automatically identify deception. In this dissertation, we identify key challenges underlying text-based deception detection in a cross-domain setting, where we do not have training data in the target domain. We analyze the differences between domains and as a result develop methods to improve cross-domain deception detection. We additionally develop approaches that take advantage of cross-lingual properties to support deception detection across languages. This involves the usage of either multilingual NLP models or translation models. Finally, to better understand multi-modal …

Coded Matrix Multiplication, Xiaodi Fan

Dissertations, Theses, and Capstone Projects

Matrix multiplication is a fundamental building block in many machine learning models. As the input matrices may be too large to be multiplied on a single server, it is common to split input matrices into multiple sub-matrices and execute the multiplications on different servers. However, in a distributed infrastructure, it is common to observe stragglers whose performance is significantly lower than other servers at some time. Compared to replicating each task on multiple servers, coded matrix multiplication, i.e., a combination of coding theoretic techniques and distributed matrix multiplication, can tolerate the same number of stragglers with much fewer servers. The …

Bitrdf: Extending Rdf For Bitemporal Data, Di Wu

Dissertations, Theses, and Capstone Projects

The Internet is not only a platform for communication, transactions, and cloud storage, but it is also a large knowledge store where people as well as machines can create, manipulate, infer, and make use of data and knowledge. The Semantic Web was developed for this purpose. It aims to help machines understand the meaning of data and knowledge so that machines can use the data and knowledge in decision making. The Resource Description Framework (RDF) forms the foundation of the Semantic Web which is organized as the Semantic Web Layer Cake. RDF is limited and can only express a binary …

Spotlight Report #6: Proffering Machine-Readable Personal Privacy Research Agreements: Pilot Project Findings For Ieee P7012 Wg, Noreen Y. Whysel, Lisa Levasseur

Publications and Research

What if people had the ability to assert their own legally binding permissions for data collection, use, sharing, and retention by the technologies they use? The IEEE P7012 has been working on an interoperability specification for machine-readable personal privacy terms to support this ability since 2018. The premise behind the work of IEEE P7012 is that people need technology that works on their behalf—i.e. software agents that assert the individual’s permissions and preferences in a machine-readable format.

Thanks to a grant from the IEEE Technical Activities Board Committee on Standards (TAB CoS), we were able to explore the attitudes of …

Happiness And Policy Implications: A Sociological View, Sarah M. Kahl

Dissertations, Theses, and Capstone Projects

The World Happiness Report is released every year, ranking each country by who is “happier” and explaining the variables and data they have used. This project attempts to build from that base and create a machine learning algorithm that can predict if a country will be in a “happy” or “could be happier” category. Findings show that taking a broader scope of variables can better help predict happiness. Policy implications are discussed in using both big data and considering social indicators to make better and lasting policies.

A Machine Learning Approach To Predicting The Onset Of Type Ii Diabetes In A Sample Of Pima Indian Women, Meriem Benarbia

Dissertations, Theses, and Capstone Projects

Type II diabetes is a disease that affects how the body regulates and uses sugar (glucose) as a fuel. This chronic disease results in too much sugar circulating in the bloodstream. High blood sugar levels can lead to circulatory, nervous, and immune systems disorders. Machine learning (ML) techniques have proven their strength in diabetes diagnosis. In this paper, we aimed to contribute to the literature on the use of ML methods by examining the value of a number of supervised machine learning algorithms such as logistic regression, decision tree classifiers, random forest classifiers, and support vector classifiers to identify factors …

Designing Respectful Tech: What Is Your Relationship With Technology?, Noreen Y. Whysel

Publications and Research

According to research at the Me2B Alliance, people feel they have a relationship with technology. It’s emotional. It’s embodied. And it’s very personal. We are studying digital relationships to answer questions like “Do people have a relationship with technology?” “What does that relationship feel like?” And “Do people understand the commitments that they are making when they explore, enter into and dissolve these relationships?” There are parallels between messy human relationships and the kinds of relationships that people develop with technology. As with human relationships, we move through states of discovery, commitment and breakup with digital applications as well. Technology …

Representation Learning For Chemical Activity Predictions, Mohamed S. Ayed

Dissertations, Theses, and Capstone Projects

Computational prediction of a phenotypic response upon the chemical perturbation on a biological system plays an important role in drug discovery and many other applications. Chemical fingerprints derived from chemical structures are a widely used feature to build machine learning models. However, the fingerprints ignore the biological context, thus, they suffer from several problems such as the activity cliff and curse of dimensionality. Fundamentally, the chemical modulation of biological activities is a multi-scale process. It is the genome-wide chemical-target interactions that modulate chemical phenotypic responses. Thus, the genome-scale chemical-target interaction profile will more directly correlate with in vitro and in …

Design And Control Of Quasi-Direct Drive Actuation For Lightweight And Versatile Wearable Robots, Shuangyue Yu

Dissertations and Theses

Wearable robots have shown great potential for augmenting the physical capabilities of humans in lab settings. However, wearable robots for augmenting the physical capabilities of humans under community-based conditions are the new frontier of robotics. Furthermore, the design and control are still considered to be grand challenges for providing physical augmentation for humans. In terms of design, the state-of-the-art exoskeletons are typically rigid, bulky, and limited to lab settings. In terms of control, most of the rhythmic controllers are not versatile and are focused only on steady-state walking assistance.

The motivation behind my research is to improve both the design …

Messiness: Automating Iot Data Streaming Spatial Analysis, Christopher White, Atilio Barreda Ii

Publications and Research

The spaces we live in go through many transformations over the course of a year, a month, or a day; My room has seen tremendous clutter and pristine order within the span of a few hours. My goal is to discover patterns within my space and formulate an understanding of the changes that occur. This insight will provide actionable direction for maintaining a cleaner environment, as well as provide some information about the optimal times for productivity and energy preservation.

Using a Raspberry Pi, I will set up automated image capture in a room in my home. These images will …

Plasmonic Field-Effect Transistors (Terafets) For 6g Communications, Michael Shur, Gregory Aizin, Taiichi Otsuji, Victor Ryzhii

Publications and Research

Ever increasing demands of data traffic makes the transition to 6G communications in the 300 GHz band inevitable. Short-channel field-effect transistors (FETs) have demonstrated excellent potential for detection and generation of terahertz (THz) and sub-THz radiation. Such transistors (often referred to as TeraFETs) include short-channel silicon complementary metal oxide (CMOS). The ballistic and quasi-ballistic electron transport in the TeraFET channels determine the TeraFET response at the sub-THz and THz frequencies. TeraFET arrays could form plasmonic crystals with nanoscale unit cells smaller or comparable to the electron mean free path but with the overall dimensions comparable with the radiation wavelength. Such …

Needle In A Haystack: Detecting Subtle Malicious Edits To Additive Manufacturing G-Code Files, Caleb Beckwith, Harsh Sankar Naicker, Svara Mehta, Viba R. Udupa, Nghia Tri Nim, Varun Gadre, Hammond Pearce, Gary Mac

Publications and Research

Increasing usage of Digital Manufacturing (DM) in safety-critical domains is increasing attention on the cybersecurity of the manufacturing process, as malicious third parties might aim to introduce defects in digital designs. In general, the DM process involves creating a digital object (as CAD files) before using a slicer program to convert the models into printing instructions (e.g. g-code) suitable for the target printer. As the g-code is an intermediate machine format, malicious edits may be difficult to detect, especially when the golden (original) models are not available to the manufacturer. In this work we aim to quantify this hypothesis through …

Inverse Kinematics Of The 6dof C12xl, Carl Liu, Lili Ma

Publications and Research

Industrial robotic manipulators are widely used in applications such as pick & place, welding, and assembly to perform repeated tasks in replace of human labor. Such tasks typically require fully autonomous mechanical arms that are capable of identifying the parts to operate, path planning, and trajectory generation & tracking. A robotic arm consists of a sequence of rigid links connected by movable components (the joints). Proper control of the arm’s motion requires the knowledge of inverse kinematics, which computes/outputs the joint variables, i.e., angles for revolute joints and displacement for prismatic joints, causing the robotic arm’s end effector (e.g., gripper, …

Efficient Protocols For Multi-Party Computation, Tahereh Jafarikhah

Dissertations, Theses, and Capstone Projects

Secure Multi-Party Computation (MPC) allows a group of parties to compute a join function on their inputs without revealing any information beyond the result of the computation. We demonstrate secure function evaluation protocols for branching programs, where the communication complexity is linear in the size of the inputs, and polynomial in the security parameter. Our result is based on the circular security of the Paillier's encryption scheme. Our work followed the breakthrough results by Boyle et al. [9; 11]. They presented a Homomorphic Secret Sharing scheme which allows the non-interactive computation of Branching Programs over shares of the secret inputs. …

Applying Deep Learning On Financial Sentiment Analysis, Cuiyuan Wang

Dissertations, Theses, and Capstone Projects

Portfolio Investment has always been appealing to investors and researchers. In the past, people tend to use historical trading information of the securities to predict the return or manage the portfolio. Nowadays, the literature has been proved that the market sentiment could predict asset prices. Specifically, it has been shown that the stock market movement is related to financial news and social media events. Thus, it becomes necessary to extract the sentiment of the financial news. We explicitly introduce the application of dictionary methods, traditional machine learning models and deep learning models on text classification. The experiment results show that …

Predicting Vasovagal Responses: A Model-Based And Machine Learning Approach, Theodore Raphan, Sergei B. Yakushi

Publications and Research

Vasovagal syncope (VVS) or neurogenically induced fainting has resulted in falls, fractures, and death. Methods to deal with VVS are to use implanted pacemakers or beta blockers. These are often ineffective because the underlying changes in the cardiovascular system that lead to the syncope are incompletely understood and diagnosis of frequent occurrences of VVS is still based on history and a tilt test, in which subjects are passively tilted from a supine position to 20◦ from the spatial vertical (to a 70◦ position) on the tilt table and maintained in that orientation for 10–15 min. Recently, is has been shown …

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 …

Cooperative Target Tracking In Concentric Formations, Lili Ma

Publications and Research

This paper considers the problem of coordinating multiple unmanned aerial vehicles (UAVs) in a circular formation around a moving target. The main contribution is allowing for versatile formation patterns on the basis of the following components. Firstly, new uniform spacing control laws are proposed that spread the agents not necessarily over a full circle, but over a circular arc. Uniform spacing formation controllers are proposed, regulating either the separation distances or the separation angles between agents. Secondly, the use of virtual agents is proposed to allow for different radii in agents’ orbits. Thirdly, a hierarchical combination of formation patterns is …

Distributed Cross-Community Collaboration For The Cloud-Based Energy Management Service, Yu-Wen Chen, J. Morris Chang

Publications and Research

Customers’ participation is a critical factor for inte-grating the distributed energy resources via demand response and demand-side management programs, especially when customers become prosumers. Incentives need to be delivered by the energy management service to attract prosumers to operate their distributed energy resources and electricity loads grid-friendly actively. The cloud-based energy management service enables virtual trading for customers within the same community to minimize cost and smooth the fluctuation. With the potential fast-growing number of service providers and customers, the needs exist for efficiently collaborating across multiple service providers and customers. This paper proposes the distributed cross-community collaboration (XCC) for …

Object Recognition And Voice Assistant With Augmented Reality, Juan Estrella

Publications and Research

Our research project aims to provide a visually impaired person with a superimposed map that will guide the individual to the desired destination through a voice controlled virtual assistant application that integrates Augmented Reality (AR) with Artificial Intelligence (AI) Computer Vision and Natural Language Processing (subfields of AI) will be combined to identify the spatial environment and then create a graphic enhancement that provides the most direct route to the specific destination These technologies will be incorporated into the Microsoft Hololens which will be controlled by the user.