Other Computer Engineering Commons^™

User Profiling Through Zero-Permission Sensors And Machine Learning, Ahmed Elhussiny

Theses and Dissertations

With the rise of mobile and pervasive computing, users are often ingesting content on the go. Services are constantly competing for attention in a very crowded field. It is only logical that users would allot their attention to the services that are most likely to adapt to their needs and interests. This matter becomes trivial when users create accounts and explicitly inform the services of their demographics and interests. Unfortunately, due to privacy and security concerns, and due to the fast nature of computing today, users see the registration process as an unnecessary hurdle to bypass, effectively refusing to provide …

A High-Speed Portable Ground Heat Exchanger Model For Use In Various Energy Simulation Software, Ryan Davies, Matt Mitchell, Edwin Lee

Macalester Journal of Physics and Astronomy

A portable component model (PCM) of a ground source heat pump system was developed and used as a test case in the creating of a PCM development framework. By developing this framework, new building energy simulation models will be able to be easily integrated into existing simulation software such as EnergyPlus and the Modelica Buildings Library. Our model uses a time responsive g-function and numerical methods to simulate ground source heat pumps for single time steps as well as long time scales. We validated our model against GHESim and GLHEPro and found that our model agrees with these two standards …

Vr Force Feedback Gloves, Mark Wu, Claire Chen

Electrical Engineering

The goal of this project is to produce a manufacturing plan for a consumer VR glove. The total addressable market of VR is over 170 million global users as of 2022 (Kolmar , 2022) with a serviceable available market of 300,000 users on Meta’s own social platform (Heath, 2022). The targeted Quest 2 platform utilizes handheld controllers, which causes a lack of immersivity in social settings and gaming scenarios. One common use of the platform involves social platforms such as “Horizons” where users meet in a virtual world to interact; handheld controllers don’t allow users to shake hands, make finger …

Sentiment Analysis Of Text And Emoji Data For Twitter Network, Paramita Dey, Soumya Dey

Al-Bahir Journal for Engineering and Pure Sciences

Twitter is a social media platform where users can post, read, and interact with 'tweets'. Third party like corporate organization can take advantage of this huge information by collecting data about their customers' opinions. The use of emoticons on social media and the emotions expressed through them are the subjects of this research paper. The purpose of this paper is to present a model for analyzing emotional responses to real-life Twitter data. The proposed model is based on supervised machine learning algorithms and data on has been collected through crawler “TWEEPY” for empirical analysis. Collected data is pre-processed, pruned and …

Credit Card Fraud Detection Using Logistic Regression And Synthetic Minority Oversampling Technique (Smote) Approach, Nrusingha Tripathy, Subrat Kumar Nayak, Julius Femi Godslove, Ibanga Kpereobong Friday, Sasanka Sekhar Dalai

International Journal of Computer and Communication Technology

Financial fraud is a serious threat that is expanding effects on the financial sector. The use of credit cards is growing as digitization and internet transactions advance daily. The most common issues in today's culture are credit card scams. This kind of fraud typically happens when someone uses someone else's credit card details. Credit card fraud detection uses transaction data attributes to identify credit card fraud, which can save significant financial losses and affluence the burden on the police. The detection of credit card fraud has three difficulties: uneven data, an abundance of unseen variables, and the selection of an …

A Study On Image Processing Techniques And Deep Learning Techniques For Insect Identification, Vinita Abhishek Gupta, M.V. Padmavati, Ravi R. Saxena, Pawan Kumar Patnaik, Raunak Kumar Tamrakar

Karbala International Journal of Modern Science

Automatic identification of insects and diseases has attracted researchers for the last few years. Researchers have suggested several algorithms to get around the problems of manually identifying insects and pests. Image processing techniques and deep convolution neural networks can overcome the challenges of manual insect identification and classification. This work focused on optimizing and assessing deep convolutional neural networks for insect identification. AlexNet, MobileNetv2, ResNet-50, ResNet-101, GoogleNet, InceptionV3, SqueezeNet, ShuffleNet, DenseNet201, VGG-16 and VGG-19 are the architectures evaluated on three different datasets. In our experiments, DenseNet 201 performed well with the highest test accuracy. Regarding training time, AlexNet performed well, …

Security-Enhanced Serial Communications, John White, Alexander Beall, Joseph Maurio, Dane Fichter, Dr. Matthew Davis, Dr. Zachary Birnbaum

Military Cyber Affairs

Industrial Control Systems (ICS) are widely used by critical infrastructure and are ubiquitous in numerous industries including telecommunications, petrochemical, and manufacturing. ICS are at a high risk of cyber attack given their internet accessibility, inherent lack of security, deployment timelines, and criticality. A unique challenge in ICS security is the prevalence of serial communication buses and other non-TCP/IP communications protocols. The communication protocols used within serial buses often lack authentication and integrity protections, leaving them vulnerable to spoofing and replay attacks. The bandwidth constraints and prevalence of legacy hardware in these systems prevent the use of modern message authentication and …

Targeted Adversarial Attacks Against Neural Network Trajectory Predictors, Kaiyuan Tan

McKelvey School of Engineering Theses & Dissertations

Trajectory prediction is an integral component of modern autonomous systems as it allows for envisioning future intentions of nearby moving agents. Due to the lack of other agents' dynamics and control policies, deep neural network (DNN) models are often employed for trajectory forecasting tasks. Although there exists an extensive literature on improving the accuracy of these models, there is a very limited number of works studying their robustness against adversarially crafted input trajectories. To bridge this gap, in this paper, we propose a targeted adversarial attack against DNN models for trajectory forecasting tasks. We call the proposed attack TA4TP for …

Enabling The Integration Of Sustainable Design Methodological Frameworks And Computational Life Cycle Assessment Tools Into Product Development Practice, Tejaswini Chatty

Dartmouth College Ph.D Dissertations

Environmental sustainability has gained critical importance in product development (PD) due to increased regulation, market competition, and consumer awareness, leading companies to set ambitious climate targets . To meet these goals, PD practitioners (engineers and designers) are often left to adapt their practices to reduce the impacts of the products they manufacture. Literature review and interviews with practitioners show that they highly valued using quantitative life cycle assessment (LCA) results to inform decision making.

LCA is a technique to measure the environmental impacts across various stages of a product life cycle. Existing LCA software tools, however, are designed for dedicated …

Grammatical Triples Extraction For The Distant Reading Of Textual Corpora, Stephanie Buongiorno, Stephanie Buongiorno

Multidisciplinary Studies Theses and Dissertations

Grammatical triples extraction has become increasingly important for the analysis of large, textual corpora. By providing insight into the sentence-level linguistic features of a corpus, extracted triples have supported interpretations of some of the most relevant problems of our time. The growing importance of triples extraction for analyzing large corpora has put the quality of extracted triples under new scrutiny, however. Triples outputs are known to have large amounts of erroneous triples. The extraction of erroneous triples poses a risk for understanding a textual corpus because erroneous triples can be nonfactual and even analogous to misinformation. Disciplines such as the …

Detection Of Crypto-Ransomware Attack Using Deep Learning, Muna Jemal

Master of Science in Computer Science Theses

The number one threat to the digital world is the exponential increase in ransomware attacks. Ransomware is malware that prevents victims from accessing their resources by locking or encrypting the data until a ransom is paid. With individuals and businesses growing dependencies on technology and the Internet, researchers in the cyber security field are looking for different measures to prevent malicious attackers from having a successful campaign. A new ransomware variant is being introduced daily, thus behavior-based analysis of detecting ransomware attacks is more effective than the traditional static analysis. This paper proposes a multi-variant classification to detect ransomware I/O …

Is Realt Reality? Investigating The Use Of Blockchain Technology And Tokenization In Real Estate Transactions, Caroline Moriarty

Minnesota Journal of Law, Science & Technology

No abstract provided.

An Investigation On The Resilience Of Long Short-Term Memory Deep Neural Networks, Christopher Vasquez

LSU Master's Theses

In a world of continuously advancing technology, the reliance on these technologies continues to increase. Recently, transformer networks [22] have been implemented through various projects such as ChatGPT. These networks are extremely computationally demanding and require cutting-edge hardware to explore. However, with the growing increase and popularity of these neural networks, a question of reliability and resilience comes about, especially as the dependency and research on these networks grow. Given the computational demand of transformer networks, we investigate the resilience of the weights and biases of the predecessor of these networks, i.e. the Long Short-Term (LSTM) neural network, through four …

Enhancing The Battleverse: The People’S Liberation Army’S Digital Twin Strategy, Joshua Baughman

Military Cyber Affairs

No abstract provided.

What Senior U.S. Leaders Say We Should Know About Cyber, Dr. Joseph H. Schafer

Military Cyber Affairs

On April 6, 2023, the Atlantic Council’s Cyber Statecraft Initiative hosted a panel discussion on the new National Cybersecurity Strategy. The panel featured four senior officials from the Office of the National Cyber Director (ONCD), the Department of State (DoS), the Department of Justice (DoJ), and the Department of Homeland Security (DHS). The author attended and asked each official to identify the most important elements that policymakers and strategists must understand about cyber. This article highlights historical and recent struggles to express cyber policy, the responses from these officials, and the author’s ongoing research to improve national security cyber policy.

Operationalizing Deterrence By Denial In The Cyber Domain, Gentry Lane

Military Cyber Affairs

No abstract provided.

Lignin Copolymer Property Prediction Using Machine Learning, Collin Larsen

Chemical Engineering Undergraduate Honors Theses

Lignin, an abundant biopolymer, is a waste byproduct of the paper and pulp industry. Despite its renewable nature and potential applicability in various products, such as plastics and composites, the development of lignin-based materials has been impeded by the cumbersome, Edisonian process of trial and error. This research proposes a novel approach to forecasting the properties of lignin-based copolymers by utilizing a recurrent neural network (RNN) based on the Keras models previously created by Tao et al. Example units of modified lignin were synthesized via esterification and amination functional group modifications. To increase the efficiency and accuracy of the prediction …

Fuel Prediction: Determining The Desirable Stops For The Cheapest Road Trips, Maxx Smith

Computer Science and Computer Engineering Undergraduate Honors Theses

Current technology has given rise to many advanced route-planning applications that are available for use by the general public. Gone are the days of preparing for road trips by looking at a paper map for hours on end trying to determine the correct exits or calculate the distance to be traveled. However, with the use of modern technology, there is a certain aspect of forward-thinking that is now lost with planning a road trip. One of the biggest constraints that often gets left on the backburner is deciding when and where to stop to refuel the car. This report is …

Svar: A Virtual Machine For Portable Code On Reconfigurable Accelerators, Nathaniel Fredricks

Computer Science and Computer Engineering Undergraduate Honors Theses

The SPAR-2 array processor was designed as an overlay architecture for implementation on Xilinx Field Programmable Gate Arrays (FPGAs). As an overlay, the SPAR-2 array processor can be configured to take advantage of the specific resources available on different FPGAs. However once configured, the SPAR-2 requires programmer’s to have knowledge of the low level architecture, and write platform-specific code. In this thesis SVAR, a hardware/software co-designed virtual machine, is proposed that runs on the SPAR-2. SVAR allows programmers to write portable, platform-independent code once and have it interpreted for any specific configuration. Results are presented that verify the virtual machine …

Culture In Computing: The Importance Of Developing Gender-Inclusive Software, Creighton France

Computer Science and Computer Engineering Undergraduate Honors Theses

The field of computing as we know it today exists because of the contributions of numerous female mathematicians, computer scientists, and programmers. While working with hardware was viewed as “a man’s job” during the mid-20th century, computing and programming was viewed as a noble and high-paying field for women to occupy. However, as time has progressed, the U.S. has seen a decrease in the number of women pursuing computer science. The idea that computing is a masculine discipline is common in the U.S. today for reasons such as male-centered marketing of electronics and gadgets, an inaccurate representation of what it …