Physical Sciences and Mathematics Commons^™

Intelligent Software Tooling For Improving Software Development, Nathan Allen Cooper

Dissertations, Theses, and Masters Projects

Software has eaten the world with many of the necessities and quality of life services people use requiring software. Therefore, tools that improve the software development experience can have a significant impact on the world such as generating code and test cases, detecting bugs, question and answering, etc. The success of Deep Learning (DL) over the past decade has shown huge advancements in automation across many domains, including Software Development processes. One of the main reasons behind this success is the availability of large datasets such as open-source code available through GitHub or image datasets of mobile Graphical User Interfaces …

Appearance Driven Reflectance Modeling, James Christopher Bieron

Dissertations, Theses, and Masters Projects

Creating realistic computer generated imagery is essential for modern movies and video games. Recreating the appearance of materials is integral to generating such photo-realistic images. While the problem of how to model materials is well studied, here we will focus on the question of how to recreate the appearance of specific materials found in the real world. In this dissertation we will begin with a short introduction to rendering, followed by a discussion of various material models, techniques for measuring reflectance, and strategies for fitting these models to reflectance data. We will then introduce a novel two-stage process for fitting, …

Program Analysis For Software Engineers And Students, Jialiang Tan

Dissertations, Theses, and Masters Projects

Software inefficiencies are inevitable in computer systems. At the code level, software packages have become increasingly complex, they are comprised of a large amount of source code, sophisticated control and data flow, and growing levels of abstraction. This complexity often introduces inefficiencies across software stacks, leading to performance degradation. At the resource level, the evolution of hardware outpaces the performance optimization of software, leading to resource wastage and energy dissipation in emerging architecture. To better understand program behaviors, software developers take advantage of performance profiling tools. Existing profiling techniques, whether fine-grained profilers or coarse-grained profilers focus on identifying hotspots, which …

Analog Holographic Wavefront Sensor For Defocus And Spherical Aberration Measurement Recorded In A Photopolymer, Emma Branigan, Suzanne Martin, Matthew Sheehan, Kevin Murphy

Articles

An analog holographic wavefront sensor (AHWFS), for measurement of low and high order (defocus and spherical aberration) aberration modes has been developed as volume phase holograms in a photopolymer recording medium. This is the first time that high order aberrations such as spherical aberration can be sensed using a volume hologram in a photosensitive medium. Both defocus and spherical aberration were recorded in a multi-mode version of this AHWFS. Refractive elements were used to generate a maximum and minimum phase delay of each aberration which were multiplexed as a set of volume phase holograms in an acrylamide based-photopolymer layer. The …

Improving The Angular Visibility Of Photopolymer-Based Reflection Holograms For Sensing Applications, Tatsiana Mikulchyk, Kevin Murphy, John Walsh, Suzanne Martin, Dervil Cody, Izabela Naydenova

Articles

Volume reflection hologram-based sensors are designed to visibly change colour in response to a target stressor or analyte. However, reflection holograms fabricated in thick photopolymer films are highly angularly selective, making these sensors challenging to view and interpret by non-experts. Here, the use of speckle holography to improve the visibility of reflection holograms is presented. A novel recording approach combining speckle recording techniques with Denisyuk reflection recording geometry is described. The recorded speckle reflection grating operates as a series of multiplexed reflection gratings with a range of spatial frequencies, capable of reflecting light at a wider range of angles. A …

Development And Evaluation Of A Multifrequency Ultrafast Doppler Spectral Analysis (Mfudsa) Algorithm For Wall Shear Stress Measurement: A Simulation And In Vitro Study, Andrew Malone, Sean Cournane, Izabela Naydenova, James F. Meaney, Andrew J. Fagan, Jacinta Browne

Articles

Cardiovascular pathology is the leading cause of death and disability in the Western world, and current diagnostic testing usually evaluates the anatomy of the vessel to determine if the vessel contains blockages and plaques. However, there is a growing school of thought that other measures, such as wall shear stress, provide more useful information for earlier diagnosis and prediction of atherosclerotic related disease compared to pulsed-wave Doppler ultrasound, magnetic resonance angiography, or computed tomography angiography. A novel algorithm for quantifying wall shear stress (WSS) in atherosclerotic plaque using diagnostic ultrasound imaging, called Multifrequency ultrafast Doppler spectral analysis (MFUDSA), is presented. …

Color-Changing Reflection Hologram For Quality Assurance Of Therapeutic Ultrasound Systems, Tatsiana Mikulchyk, John Walsh, Jacinta Browne, Izabela Naydenova, Dervil Cody

Articles

The acoustic output of clinical therapeutic ultrasound equipment requires regular quality assurance (QA) testing to ensure the safety and efficacy of the treatment and that any potentially harmful deviations from the expected output power density are detected as soon as possible. A hologram, consisting of a reflection grating fabricated in an acrylate photopolymer film, has been developed to produce an immediate, visible, and permanent change in the color of the reconstructed hologram from red to green in response to incident ultrasound energy. The influence of the therapeutic ultrasound insonation parameters (exposure time, ultrasound power density, and proximity to the point …

Njit Makerspace For K-8, Joya Clark

STEM for Success Resources

Ideas for Cultivating a Makerspace Mindset in K-8 students, By Joya Clark; Curriculum Specialist, Robotics Coach, STEM teacher

Credit Worthiness Tool For Credit Unions, Rylee Christoffersen, Mario Ramalho

ICT

The core objectives for the Capstone project were to mine data in order to create a tool for Credit Unions (and banks) that will evaluate customers credit worthiness based on an ethical standardised criteria that is transparent to all. We explored why this was necessary and explored how important it could be to the business. Our focus is on helping Credit Unions have a stronger online presence as the banking sector has been changing rapidly and moving online and Credit Unions are currently behind in the market in this regard .This tool would help automate the credit approval process, reducing …

Facial Recognition Using Neural Network, Georges Diego Hawile Pinheiro, Allison Alves De Moura

ICT

Face recognition technology using machine learning and neural networks has become increasingly prevalent in recent years, revolutionizing various fields such as security, law enforcement, and marketing. The development of an AI-based system that can perform face recognition using these technologies has become a significant focus for researchers and developers worldwide. This project aims to create such a system that can recognize and classify faces accurately using machine learning algorithms and neural networks. By leveraging these advanced technologies, the system can learn and improve over time, leading to higher accuracy rates and enhanced performance.

Predicting The Effects Of Climate Change On Irish Agriculture, Rodrigo Matsumoto, Sarah Kuprian Carrinho

ICT

The impact of climate change on agriculture is a growing concern worldwide, and Ireland is no exception. The purpose of this project is to use machine learning techniques to predict the effects of climate change on Irish agriculture and identify strategies for adaptation and mitigation. The project uses the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology to guide the data analysis process, MoSCoW prioritization to identify the most critical needs, and SWOT analysis to evaluate the strengths, weaknesses, opportunities, and threats our project may encounter. Historical temperature data for Ireland and Dublin will be used as our data sources. …

Fake News Detection Using Natural Language Processing, Fabiolla Mayrink Costa, Rael Guimaraes

ICT

Nowadays with the advance of technologies we have vast access to any sort of information. We are able to use our phone/computer to access the news of any part of the world. It is great to keep us informed about everything that is happening around the world. It is also a powerful tool used for companies while making strategic business decisions. The biggest issue is that technology can and is being used to manipulate people/companies by propagating fake news. Fake news can mislead people's perceptions while forming opinions on a determined subject. It can also have a big impact on …

Menu Recommendation System Using Machine Learning, Kelly Crystine Ferreira Jesus, Leo Jaime Kayser Macieski

ICT

Developing a recommendation menu system for restaurants based on the restaurant data and/or city food purchase data to help and change the way restaurants build their menu. Using Data Analysis and Machine Learning to build a project that aims to solve the problem of restaurants and chefs when it comes to preparing menus, the latter with ingredients and dishes that encourage their customers to order more, come back and recommend the restaurant. Helping chefs to create dishes for their restaurants with more accuracy and higher probability to be ordered by their customers. The project will cover tools to build the …

Robust Cache System For Web Search Engine Yioop, Rushikesh Padia

Master's Projects

Caches are the most effective mechanism utilized by web search engines to optimize the performance of search queries. Search engines employ caching at multiple levels to improve its performance, for example, caching posting list and caching result set. Caching query results reduces overhead of processing frequent queries and thus saves a lot of time and computing power. Yioop is an open-source web search engine which utilizes result cache to optimize searches. The current implementation utilizes a single dynamic cache based on Marker’s algorithm. The goal of the project is to improve the performance of cache in Yioop. To choose a …

Enhancing Facial Emotion Recognition Using Image Processing With Cnn, Sourabh Deokar

Master's Projects

Facial expression recognition (FER) has been a challenging task in computer vision for decades. With recent advancements in deep learning, convolutional neural networks (CNNs) have shown promising results in this field. However, the accuracy of FER using CNNs heavily relies on the quality of the input images and the size of the dataset. Moreover, even in pictures of the same person with the same expression, brightness, backdrop, and stance might change. These variations are emphasized when comparing pictures of individuals with varying ethnic backgrounds and facial features, which makes it challenging for deep-learning models to classify. In this paper, we …

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 …

Hate Speech Detection In Hindi, Pranjali Prakash Bansod

Master's Projects

Social media is a great place to share one’s thoughts and to express oneself. Very often the same social media platforms become a means for spewing hatred.The large amount of data being shared on these platforms make it difficult to moderate the content shared by users. In a diverse country like India hate is present on social media in all regional languages, making it even more difficult to detect hate because of a lack of enough data to train deep/ machine learning models to make them understand regional languages.This work is our attempt at tackling hate speech in Hindi. We …

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 …

Insecure Deserialization Detection In Python, Aneesh Verma

Master's Projects

The importance of Cyber Security is increasing every single day. From the emergence of new ransomware to major data breaches, the online world is getting dangerous. A multinational non- profit group devoted to online application security is called OWASP, or the Open Web Application Security Project. The OWASP Top 10 is a frequently updated report that highlights the ten most important vulnerabilities to web application security. Among these 10 vulnerabilities, there exists a vulnerability called Software and Data Integrity Failures. A subset of this vulnerability is Insecure Deserialization. An object is transformed into a stream of bytes through the serialization …

Application Of Adversarial Attacks On Malware Detection Models, Vaishnavi Nagireddy

Master's Projects

Malware detection is vital as it ensures that a computer is safe from any kind of malicious software that puts users at risk. Too many variants of these malicious software are being introduced everyday at increased speed. Thus, to guarantee security of computer systems, huge advancements in the field of malware detection are made and one such approach is to use machine learning for malware detection. Even though machine learning is very powerful, it is prone to adversarial attacks. In this project, we will try to apply adversarial attacks on malware detection models. To perform these attacks, fake samples that …

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 …

Personalized Tweet Recommendation Using Users’ Image Preferences, Shashwat Avinash Kadam

Master's Projects

In the era of information explosion, the vast amount of data on social media platforms can overwhelm users. Not only does this information explosion contain irrelevant content, but also intentionally fabricated articles and images. As a result, personalized recommendation systems have become increasingly important to help users navigate and make sense of this data. We propose a novel technique to use users’ image preferences to recommend tweets. We extract vital information by analyzing images liked by users and use it to recommend tweets from Twitter. As many images online have no descriptive metadata associated with them, in this framework, we …

Explainable Ai For Android Malware Detection, Maithili Kulkarni

Master's Projects

Android malware detection based on machine learning (ML) is widely used by the mobile device security community. Machine learning models offer benefits in terms of detection accuracy and efficiency, but it is often difficult to understand how such models make decisions. As a result, popular malware detection strategies remain black box models, which may result in a lack of accountability and trust in the decisions made. The field of explainable artificial intelligence (XAI) attempts to shed light on such black box models. In this research, we apply XAI techniques to ML-based Android malware detection systems. We train classic ML models …

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 …

Base Station Load Prediction In 5g-V2x Handover, Madhujita Ranjit Ambaskar

Master's Projects

5G V2X networks transmit large amounts of data with low latency, allowing for real-time communication between vehicles and other infrastructure. In 5G V2X networks, handover is a process that allows a connected vehicle to transfer its con- nection from one base station to another as it moves through the network coverage area. Handover is critical to maintaining the quality of service (QoS) and ensuring uninterrupted communication. The base station load is a critical factor in ensuring reliable and efficient 5G V2X connectivity. Prediction of traffic load on base stations ensure resource optimization and smooth connectivity during handovers. This research predicts …

Context Aware Neural Machine Translation Using Graph Encoders, Saurabh Kale

Master's Projects

Machine translation presents its root in the domain of textual processing that focuses on the usage of computer software for the purpose of translation of sentences. Neural machine translation follows the same idea and integrates machine learning with the help of neural networks.Various techniques are being explored by researchers and are famously used by Google Translate, Bing Microsoft Translator, Deep Translator, etc. However, these neural machine translation techniques do not incorporate the context of the sentences and are only determined by the phrasesor sentence structure. This report explores the neural machine translation technique dedicated to context-aware translations. It also provides …

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. …

Macruby: User Defined Macro Support For Ruby, Arushi Singh

Master's Projects

Ruby does not have a way to create custom syntax outside what the language already offers. Macros allow custom syntax creation. They achieve this by code generation that transforms a small set of instructions into a larger set of instructions. This gives programmers the opportunity to extend the language based on their own custom needs.

Macros are a form of meta-programming that helps programmers in writing clean and concise code. MacRuby is a hygienic macro system. It works by parsing the Abstract Syntax Tree(AST) and replacing macro references with expanded Ruby code. MacRuby offers an intuitive way to declare macro …

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 …

Image Classification Using Ensemble Modeling And Deep Learning, Kaneesha Gandhi

Master's Projects

With the advances in technology, image classification has become one of the core areas of interest for researchers in the field of computer vision. We, humans, experience great levels of visuals in our day-to-day lives. The human eye is a powerful tool that not only lets us capture images around us but also aids in remembering, distinguishing, and interpreting these visuals. Comprehending the images that the user perceives is an important application in the fields of artificial intelligence, smart security systems, and areas of virtual reality. Recent advances in machine learning and neural networks have led to more precise and …