Physical Sciences and Mathematics Commons^™

Ubiquitous Application Data Collection In A Disconnected Distributed System, Deepak Munagala

Master's Projects

Despite some incredible advancements in technology, a significant population of the world does not have internet connectivity. These people lack access to crucial information that is easily available to the rest of the world. To solve this problem, we implement a Delay Tolerant Network (DTN) that allows users in disconnected regions access to the internet. This is enabled by collecting all data requests on the users’ phones and passing them to a device that can carry them to a connected region. This device can then collect the necessary information and give it back to the users in the disconnected region. …

Visualizing Classification Errors And Mislabeling In Machine Learning, Vedashree Bhandare

Master's Projects

Deep neural networks have gained popularity and achieved high performance across multiple domains like medical decision-making, autonomous vehicles, decision support systems, etc. Despite this achievement, the internal workings of these models are opaque and are considered as black boxes due to their nested and non-linear structure. This opaque nature of the deep neural networks makes it difficult to interpret the reason behind their output, thus reducing trust and verifiability of the system where these models are applied. This paper explains a systematic approach to identify the clusters with most misclassifications or false label annotations. For this research, we extracted the …

Application Of Knowledge Graph Techniques On Textbooks, Yutong Yao

Master's Projects

Textbooks are written and organized in a way that facilitates learning and understanding. Sections like glossary terms at the end of a textbook provide guidance on the topic of interest. However, it takes manual effort to create the index terms in the glossary that highlight the key referenced terminologies and related terms. Knowledge graphs, which have been used to represent and even reason over data and knowledge, can potentially capture textbook’s important terms, concepts, and their relations. Popular since the initial introduction by Google Knowledge Graphs (KGs), they combine graph and data to capture and model enormous amounts of relational …

Spartanscript: New Language Design For Smart Contracts, Ajinkya Lakade

Master's Projects

Smart contracts have become a crucial element for developing decentralized applications on blockchain, resulting in numerous innovative projects on blockchain networks. Ethereum has played a significant role in this space by providing a high-performance Ethereum virtual machine, enabling the creation of several high- level programming languages that can run on the Ethereum blockchain. Despite its usefulness, the Ethereum Virtual Machine has been prone to security vulnerabilities that can result in developers succumbing to common pitfalls which are otherwise safeguarded by modern virtual machines used in programming languages. The project aims to introduce a new interpreted scripting programming language that closely …

Influence Maximization Based On Community Detection And Dominating Sets, Ameya Marathe

Master's Projects

An online platform where various people come together to share information and communicate is called a social network. These platforms are set apart from other means of communication mostly because you can follow and interact also with different people even some you never met, comment on their posts, and re-sharing their posts. Companies such as Amazon and Walmart use these platforms daily for marketing purposes, like spreading information regarding new products and services they offer. They carefully select a subset of users, called influencers, who are usually the ones with high influence over the rest of the users. Influencers receive …

Spartan Price Oracle: A Schelling-Point Based Decentralized Pirce Oracle, Sihan He

Master's Projects

Nakamoto’s Bitcoin is the first decentralized digital cash system that utilizes a blockchain to manage transactions in its peer-to-peer network. The newer generation of blockchain systems, including Ethereum, extend their capabilities to support deployment of smart contracts within their peer-to-peer networks. However, smart contracts cannot acquire data from sources outside the blockchain since the blockchain network is isolated from the outside world. To obtain data from external sources, smart contracts must rely on Oracles, which are agents that bring data from the outside world to a blockchain network. However, guaranteeing that the oracle’s off-chain nodes are trustworthy remains a challenge. …

Nft Artifact Prediction Using Machine Learning, Rishabh Pandey

Master's Projects

NFT Prediction Systems are web applications that provide their users with valuable insights about the artifact. These insights are useful for investors and collectors to make better decisions about their purchases. This project builds upon the same concept of prediction by developing a web application to dynamically provide recommendations based on user input and training an ML model to predict their cost. Preliminary work for the prediction system involved data collection, pre-processing, analysis, and filtering of large datasets from diverse sources. The project focused on the development of a user- friendly UI to enable seamless categorization of search results generated …

Gender Classification Via Human Joints Using Convolutional Neural Network, Cheng-En Sung

Master's Projects

With the growing demand for gender-related data on diverse applications, including security systems for ascertaining an individual’s identity for border crossing, as well as marketing purposes of digging the potential customer and tailoring special discounts for them, gender classification has become an essential task within the field of computer vision and deep learning. There has been extensive research conducted on classifying human gender using facial expression, exterior appearance (e.g., hair, clothes), or gait movement. However, within the scope of our research, none have specifically focused gender classification on two-dimensional body joints. Knowing this, we believe that a new prediction pipeline …

Dynamic Predictions Of Thermal Heating And Cooling Of Silicon Wafer, Hitesh Kumar

Master's Projects

Neural Networks are now emerging in every industry. All the industries are trying their best to exploit the benefits of neural networks and deep learning to make predictions or simulate their ongoing process with the use of their generated data. The purpose of this report is to study the heating pattern of a silicon wafer and make predictions using various machine learning techniques. The heating of the silicon wafer involves various factors ranging from number of lamps, wafer properties and points taken in consideration to capture the heating temperature. This process involves dynamic inputs which facilitates the heating of the …

Automated Evaluation For Distributed System Assignments, Nimesh Nischal

Master's Projects

A distributed system can exist in numerous states, including many erroneous permutations that could have been addressed in the code. As distributed systems such as cloud computing and microservices gain popularity, involving distributed com- puting assignments is becoming increasingly crucial in Computer Science and related fields. However, designing such systems poses various challenges, such as considering parallel executions, error-inducing edge cases, and interactions with external systems. Typically, distributed assignments require students to implement a system and run multiple instances of the same code to behave as distributed. However, such assign- ments do not encourage students to consider the potential edge …

Proof-Of-Stake For Spartangold, Nimesh Ashok Doolani

Master's Projects

Consensus protocols are critical for any blockchain technology, and Proof-of- Stake (PoS) protocols have gained popularity due to their advantages over Proof-of- Work (PoW) protocols in terms of scalability and efficiency. However, existing PoS mechanisms, such as delegated and bonded PoS, suffer from security and usability issues. Pure PoS (PPoS) protocols provide a stronger decentralization and offer a potential solution to these problems. Algorand, a well-known cryptocurrency, employs a PPoS protocol that utilizes a new Byzantine Agreement (BA) mechanism for consensus and Verifiable Random Functions (VRFs) to securely scale the protocol to accommodate many participants, making it possible to handle …

Codeval, Aditi Agrawal

Master's Projects

Grading coding assignments call for a lot of work. There are numerous aspects of the code that need to be checked, such as compilation errors, runtime errors, the number of test cases passed or failed, and plagiarism. Automated grading tools for programming assignments can be used to help instructors and graders in evaluating the programming assignments quickly and easily. Creating the assignment on Canvas is again a time taking process and can be automated. We developed CodEval, which instantly grades the student assignment submitted on Canvas and provides feedback to the students. It also uploads, creates, and edits assignments, thereby …

Relationalnet Using Graph Neural Networks For Social Recommendations, Dharahas Tallapally

Master's Projects

Traditional recommender systems create models that can predict user interests based on the user-item relationships. However, these systems often have limited performance due to sparse user behavior data. To address this challenge, researchers are now exploring models for social recommendation that can account for both user- user and user-item relationships based on social networks, and user past behavior, respectively. These models aim to understand each user’s behavior by considering their trusted neighbors and their influence on each other. Specifically, the potential embedding of each user is influenced by their trusted neighbors, who are, in turn, influenced by their own trusted …

Airport Assignment For Emergency Aircraft Using Reinforcement Learning, Saketh Kamatham

Master's Projects

The volume of air traffic is increasing exponentially every day. The Air Traffic Control (ATC) at the airport has to handle aircraft runway assignments for landing and takeoff and airspace maintenance by directing passing aircraft through the airspace safely. If any aircraft is facing a technical issue or problem and is in a state of emergency, it requires expedited landing to respond to that emergency. The ATC gives this aircraft priority to landing and assistance. This process is very strenuous as the ATC has to deal with multiple aspects along with the emergency aircraft. It is the duty of the …

Rideshare Using Degrees Of Separation: A Social Network-Based Approach, Gokul Garikipati

Master's Projects

Conventional ride-sharing services, such as Lyft and Uber, routinely match drivers with riders based on their proximity to each other, using GPS coordinates and mapping technology. The application then calculates the cost of the ride based on factors such as distance traveled and time spent in the car. The concept of six degrees of separation suggests that a maximum of 6 steps or relationships can connect any two individuals in the world. This idea could be applied to a ride-share service to provide a more personalized and efficient experience for users. Instead of just matching riders with drivers based on …

The New Student: The Enhancement Of An Ebook To Support Emotional Connection, Rebecca Zumaeta

Master's Projects

EBooks are a form of multimedia applications that encourage cognitive learning. Multimedia can also influence readers to have a deeper connection to the story. Understanding the influence of a static picture book versus an animated and audio guided eBook can prove valuable in developing learning media and other forms of content. In this research we take a published children's book and apply the content into a multimedia eBook. The purpose of the creation of the eBook is to compare the interest of a reader on a story when static format, when some multimedia is added and when the story is …

High Performance Distributed File System Based On Blockchain, Ajinkya Rajguru

Master's Projects

Distributed filesystem architectures use commodity hardware to store data on a large scale with maximum consistency and availability. Blockchain makes it possible to store information that can never be tampered with and incentivizes a traditional decentralized storage system. This project aimed to implement a decentralized filesystem that leverages the blockchain to keep a record of all the transactions on it. A conventional filesystem viz. GFS [1] or HDFS [2] uses designated servers owned by their organization to store the data and are governed by a master service. This project aimed at removing a single point of failure and makes use …

Twitter Bot Detection Using Nlp And Graph Classification, Warada Jayant Kulkarni

Master's Projects

Social media platforms are one of the primary resources for information as it is easily accessible, low in cost, and provides a high rate of information spread. Online social media (OSM) have become the main source of news information around the world, but because of the distributed nature of the web, it has increased the risk of fake news spread. Fake news is misleading information that is published as real news. Therefore, identifying fake news and flagging them as such, as well as detecting sources that generate them is an ongoing task for researchers and OSM companies. Bots are artificial …

Federated Learning For Protecting Medical Data Privacy, Abhishek Reddy Punreddy

Master's Projects

Deep learning is one of the most advanced machine learning techniques, and its prominence has increased in recent years. Language processing, predictions in medical research and pattern recognition are few of the numerous fields in which it is widely utilized. Numerous modern medical applications benefit greatly from the implementation of machine learning (ML) models and the disruptive innovations in the entire modern health care system. It is extensively used for constructing accurate and robust statistical models from large volumes of medical data collected from a variety of sources in contemporary healthcare systems [1]. Due to privacy concerns that restrict access …

Proxy Re-Encryption In Blockchain-Based Application, Wangcheng Yuan

Master's Projects

Nowadays, blockchain-based technology has risen to a new dimension. With the advantage of the decentralized identity, data are transferred through decentralized and public ledgers. Those new contracts provide great visibility. However, there is still a need to keep some data private in many cases. Those private data should be encrypted while still benefiting from the decentralized on-chain protocol. Securing those private data in such a decentralized blockchain-based system is thus a critical problem. Our solution provides a decentralized protocol that lets users grant access to their private data with proxy re-encryption in SpartanGold (a blockchain-based cryptocurrency). We implement a third-party …

Codis: Community Detection Via Distributed Seed-Set Expansion On Graph Streams, Austin Anderson

Master's Projects

Community detection has been and remains a very important topic in several fields. From marketing and social networking to biological studies, community detec- tion plays a key role in advancing research in many different fields. Research on this topic originally looked at classifying nodes into discrete communities, but eventually moved forward to placing nodes in multiple communities. Unfortunately, community detection has always been a time-inefficient process, and recent data sets have been simply to large to realistically process using traditional methods. Because of this, recent methods have turned to parallelism, but all these methods, while offering sig- nificant decrease in …

Empirical Evaluation Of The Shift And Scale Parameters In Batch Normalization, Yashna Peerthum

Master's Projects

Batch Normalization (BatchNorm) is a technique that enables the training of deep neural networks, especially Convolutional Neural Networks (CNN) for computer vision tasks. It has been empirically demonstrated that BatchNorm increases per- formance, stability, and accuracy, although the reasons for these improvements are unclear. BatchNorm consists of a normalization step with trainable shift and scale parameters. In this paper, we examine the role of normalization and the shift and scale parameters in BatchNorm. We implement two new optimizers in PyTorch: a version of BatchNorm that we refer to as AffineLayer, which includes the shift and scale transform without normalization, and …

Canvas Autoquiz, Archit Jain

Master's Projects

Online learning management platforms such as Canvas are thriving and quickly replacing traditional classrooms, especially during these pandemic-struck times. As more and more quizzes are administered online, we need tools that make the quiz creation process easier and faster. Canvas Autoquiz is a command-line tool that allows instructors to automatically create and upload quizzes of varying difficulty levels. It also allows instructors to export quizzes from one LMS platform to another. This project explores the need, design, and implementation of the tool, and prospective future work.

Poriferal Vision: Deep Transfer Learning-Based Sponge Spicules Identification & Taxonomic Classification, Sudhin Domala

Master's Projects

The phylum Porifera includes the aquatic organisms known as sponges. Sponges are classified into four classes: Calcarea, Hexactinellida, Demospongiae, and Homoscleromorpha. Within Demospongiae and Hexactinellida, sponges’ skeletons are needle-like spicules made of silica. With a wide variety of shapes and sizes, these siliceous spicules’ morphology plays a pivotal role in assessing and understanding sponges' taxonomic diversity and evolution. In marine ecosystems, when sponges die their bodies disintegrate over time, but their spicules remain in the sediments as fossilized records that bear ample taxonomic information to reconstruct the evolution of sponge communities and sponge phylogeny.

Traditional methods of identifying spicules from …

Virtual Machine For Spartangold, William Wang

Master's Projects

The field of blockchain and cryptocurrencies can be both difficult to grasp and improve upon, which makes aids that can assist in these tasks very useful. SpartanGold is a simplified blockchain-based cryptocurrency created at San Jose State University as a learning aid for blockchain and cryptocurrencies. In its current state, it closely resembles Bitcoin, and it is also easily expandable to implement other features.

This project extends SpartanGold with a virtual machine resembling the Ethereum Virtual Machine. Implementing this feature results in SpartanGold having Ethereum- related features, which would allow the cryptocurrency to both be a helpful learning aid for …

Analysis Of Public Sentiment Of Covid-19 Pandemic, Vaccines, And Lockdowns, Devinesh Singh

Master's Projects

CoV-2 pandemic prompted lockdown measures to be implemented worldwide; these directives were implemented nationwide to stunt the spread of the infection. Throughout the lockdowns, millions of individuals resorted to social media for entertainment, communicate with friends and family, and express their opinions about the pandemic. Simultaneously, social media aided in the dissemination of misinformation, which has proven to be a threat to global health. Sentiment analysis, a technique used to analyze textual data, can be used to gain an overview of public opinion behind CoV-2 from Twitter and TikTok. The primary focus of the project is to build a deep …

Evaluation Of Gpu Acceleration For Wrf–Sfire, Joshua Benz

Master's Projects

WRF–SFIRE is an open source, atmospheric–wildfire model that couples the WRF model with the level set fire spread model to simulate wildfires in real time. This model has many applications and more scientific questions can be asked and answered if the model can be run faster. Nvidia has put a lot of effort into easing the barrier of entry for accelerating applications with their tools to be run on GPUs. Various physical simulations have been successfully ported to utilize GPUs and have benefited from the speed increase. In this research, we take a look at WRF-SFIRE and try to use …

Nitrogenase Iron Protein Classification Using Cnn Neural Network, Amer Rez

Master's Projects

The nitrogenase iron protein (NifH) is extensively used to study nitrogen fixation, the ecologically vital process of reducing atmospheric nitrogen to a bioavailable form. The discovery rate of novel NifH sequences is high, and there is an ongoing need for software tools to mine NifH records from the GenBank repository. Since record annotations are unreliable, because they contain errors, classifiers based on sequence alone are required. The ARBitrator classifier is highly successful but must be initialized by extensive manual effort. A Deep Learning approach could substantially reduce manual intervention. However, attempts to build a character-based Deep Learning NifH classifier were …

Proquest Tdm Studio: A Text And Data Mining Solution, Anamika Megwalu, Anne Marie Engelsen

Faculty Research, Scholarly, and Creative Activity

TDM Studio is an integrated platform offered by ProQuest for data and text mining. TDM stands for text and data mining. This cloud-based, all-in-one innovative product is designed to offer researchers a clean interface with rights-cleared content, Jupyter notebook, and data visualization tools. As a result, researchers can now search Pro-Quest databases, create large datasets, import data to Jupyter notebook for analysis, and download results within a day.

Advancing The Ability To Predict Cognitive Decline And Alzheimer’S Disease Based On Genetic Variants Beyond Amyloid-Beta And Tau, Naveen Rawat

Master's Projects

A growing amount of neurodegenerative R&D is focused on identifying genomic- based explanations of AD that are beyond Amyloid-b and Tau. The proposed effort involves identifying some of the genomic variations, such as single nucleotide polymorphisms (SNPs), allele , chromosome, epigenetic contributors to MCI and AD that are beyond Aβ and Tau.

The project involves building a prediction model based on a support vector machine (SVM) classifier that takes into account the genomic variations and epigenetic factors to predict the early stage of mild cognitive impairment (MCI) and Alzheimer disease (AD). To achieve this, picking up important feature sets which …