Physical Sciences and Mathematics Commons^™

Machine Learning To Detect Malware Evolution, Lolitha Sresta Tupadha

Master's Projects

Malware evolves over time and anti-virus must adapt to such evolution. Hence, it is critical to detect those points in time where malware has evolved so that appro-priate countermeasures can be undertaken. In this research, we perform a variety of experiments to determine when malware evolution is likely to have occurred. All of the evolution detection techniques that we consider are based on machine learning and can be fully automated—in particular, no reverse engineering or other labor-intensive manual analysis is required. Specifically, we consider analysis based on hidden Markov models and various word embedding techniques, among other machine learning based …

Higher-Order Link Prediction Using Node And Subgraph Embeddings, Kalpnil Anjan

Master's Projects

Social media, academia collaborations, e-commerce websites, biological structures, and other real-world networks are modeled as graphs to represent their entities and relationships in an abstract way. Such graphs are becoming more complex and informative, and by analyzing them we can solve various problems and find hidden insights. Some applications include predicting relationships and potential links between nodes, classifying nodes, and finding the most influential nodes in the graph, etc.

A large amount of research is being done in the field of predicting links between two nodes. However, predicting a future relationship among three or more nodes in a graph is …

Image-Based Real Estate Appraisal Using Cnns And Ensemble Learning, Prathamesh Dnyanesh Kumkar

Master's Projects

Real Estate Appraisal is performed to evaluate properties during a range of activities like buying, selling, mortgaging, or insuring. Traditionally, this process is done by real estate brokers who consider factors like the location of a house, its area, the number of bedrooms and bathrooms, along with other amenities to assess the property. This approach is quite subjective since different brokers may arrive at a different quote for the same property depending on their analysis. The development in machine learning algorithms has given rise to several Automated Valuation Models (AVMs) to estimate real estate prices. Real estate websites use such …

Fake Malware Classification With Cnn Via Image Conversion: A Game Theory Approach, Yash Sahasrabuddhe

Master's Projects

Improvements in malware detection techniques have grown significantly over the past decade. These improvements have resulted in better security for systems from various forms of malware attacks. However, it is also the reason for continuous evolution of malware which makes it harder for current security mechanisms to detect them. Hence, there is a need to understand different malwares and study classification techniques using the ever-evolving field of machine learning. The goal of this research project is to identify similarities between malware families and to improve on classification of malwares within different malware families by implementing Convolutional Neural Networks (CNNs) on …

Malware Analysis With Auxiliary-Classifier Gan, Rakesh Nagaraju

Master's Projects

A generative adversarial network (GAN) is a powerful machine learning concept where both a generative and discriminative model are trained simultaneously. A recent trend in malware research consists of treating executables as images and employing image-based analysis techniques. In this research, we generate fake malware images using GANs, and we also consider the effectiveness of GANs for malware classification. Specifically, we consider auxiliary classifier GAN (AC-GAN), which enables us to work with multiclass data. We find that AC-GAN generates malware images that cannot be reliably distinguished from real malware images. In addition, we find that the detection capabilities of AC-GAN …

Hidden Markov Model-Based Clustering For Malware Classification, Shamli Singh

Master's Projects

Automated techniques to classify malware samples into their respective families are critical in cybersecurity. Previously research applied ��-means clustering to scores generated by hidden Markov models (HMM) as a means of dealing with the malware classification problem. In this research, we follow a somewhat similar approach, but instead of using HMMs to generate scores, we directly cluster the HMMs themselves. We obtain good results on a challenging malware dataset.

Cyberbullying Classification Based On Social Network Analysis, Anqi Wang

Master's Projects

With the popularity of social media platforms such as Facebook, Twitter, and Instagram, people widely share their opinions and comments over the Internet. Exten- sive use of social media has also caused a lot of problems. A representative problem is Cyberbullying, which is a serious social problem, mostly among teenagers. Cyber- bullying occurs when a social media user posts aggressive words or phrases to harass other users, and that leads to negatively affects on their mental and social well-being. Additionally, it may ruin the reputation of that media. We are considering the problem of detecting posts that are aggressive. Moreover, …

Overlapping Community Detection In Social Networks, Akshar Panchal

Master's Projects

Social networking sites are important to connect with the world virtually. As the number of users accessing these sites increase, the data and information keeps on increasing. There are communities and groups which are formed virtually based on different factors. We can visualize these communities as networks of users or nodes and the relationships or connections between them as edges. This helps in evaluating and analyzing different factors that influence community formation in such a dense network. Community detection helps in revealing certain characteristics which makes these groups in the network unique and different from one another. We can use …

Wildfire Risk Prediction For A Smart City, Rekha Rani

Master's Projects

Wildfires are uncontrolled fires that may lead to the destruction of biodiversity, soil fertility, and human resources. There is a need for timely detection and prediction of wildfires to minimize their disastrous effects. In this research, we propose a wildfire prediction model that relies on multi-criteria decision making (MCDM) to explicitly evaluates multiple conflicting criteria in decision making and weave the wildfire risks into the city’s resiliency plan. We incorporate fuzzy set theory to handle imprecision and uncertainties. In the process, we create a new data set that includes California cities’ weather, vegetation, topography, and population density records. The model …

Fake News Analysis And Graph Classification On A Covid-19 Twitter Dataset, Kriti Gupta

Master's Projects

Earlier researches have showed that the spread of fake news through social media can have a huge impact to society and also to individuals in an extremely negative way. In this work we aim to study the spread of fake news compared to real news in a social network. We do that by performing classical social network analysis to discover various characteristics, and formulate the problem as a binary classification, where we have graphs modeling the spread of fake and real news. For our experiments we rely on how news are propagated through a popular social media services such as …

Data Augmentation With Malware As Images, Aditi Walia

Master's Projects

Machine learning and deep learning techniques for malware detection and classifi- cation play an important role in the mitigation of cybersecurity threats. However, such techniques are often limited by a lack of data. Previous research has shown promising classification results by treating malware executables as images. In this research, we consider data augmentation using noise addition, geometric transforma- tions, and Auxiliary Classifier Generative Adversarial Networks (AC-GAN) for data augmentation of malware images. We train convolution neural networks (CNN) to verify that our generated images accurately model the original malware samples.

Presentation Attack Detection In Facial Biometric Authentication, Hardik Kumar

Master's Projects

Biometric systems are referred to those structures that enable recognizing an individual, or specifically a characteristic, using biometric data and mathematical algorithms. These are known to be widely employed in various organizations and companies, mostly as authentication systems. Biometric authentic systems are usually much more secure than a classic one, however they also have some loopholes. Presentation attacks indicate those attacks which spoof the biometric systems or sensors. The presentation attacks covered in this project are: photo attacks and deepfake attacks. In the case of photo attacks, it is observed that interactive action check like Eye Blinking proves efficient in …

Can Parallel Gravitational Search Algorithm Effectively Choose Parameters For Photovoltaic Cell Current Voltage Characteristics?, Alan Kirkpatrick

Honors Projects

This study asks the question “Can parallel Gravitational Search Algorithm (GSA) effectively choose parameters for photovoltaic cell current voltage characteristics?” These parameters will be plugged into the Single Diode Model to create the IV curve. It will also investigate Particle Swarm Optimization (PSO) and a population based random search (PBRS) to see if GSA performs the search better and or more quickly than alternative algorithms

Experiment Of Leymus Chinensis In Raising Diary Cows, Xiaoliang Lu, Lu Qin, Zhu Liang

IGC Proceedings (1993-2023)

No abstract provided.

The Effect Of Applying Lactic Acid Bacteria To Elymus Excelsus And Elymus Sibiricus Gramineous Mixed Grass On Fermentation Characteristics, Hanlu Liu, Rong Gui, Na Ta, Rihua Wei

IGC Proceedings (1993-2023)

No abstract provided.

Effects Of Lactic Acid Bacteria And Cellulases On The Quality Of Ensiled Wheat Straw, Yongzhi Liu, B. W. Chang

IGC Proceedings (1993-2023)

No abstract provided.

Anticipating Linear Stochastic Differential Equations With Adapted Coefficients, Hui-Hsiung Kuo, Pujan Shrestha, Sudip Sinha

Journal of Stochastic Analysis

No abstract provided.

Teacher Background Knowledge: Biodiversity, Center For Urban Resilience

Module 06: Urban Biodiversity

No abstract provided.

Distribution And Frequency Of Aquatic Oomycetes Throughout Marin County In Relation To Physical Chemical Water Parameters, Franki Crites

Natural Sciences and Mathematics | Biological Sciences Master's Theses

Oomycetes, also known as water molds, belong to the kingdom Stramenopila and are a well-known group of plant pathogens and saprophytes. Important species include Phytophthora ramorum (causal agent of sudden oak death), Pythium aphanidermatum (root rot), and Phytophthora infestans (late potato blight), all major threats to the environment, agriculture, and the economy. Although many oomycete species have been found in various water sources, little is known about the correlation between the distribution and frequency of oomycetes in aquatic environments and physical chemical water parameters. The objective of this study was to detect and identify aquatic oomycetes from Marin County using …

Interferometric Imaging Of Λ Andromedae: Evidence Of Starspots And Rotation, J. Robert Parks, Russel J. White, Frédérique Baron, John D. Monnier, Brian Kloppenborg, Gregory W. Henry, Gail Schaefer, Xiao Che, Ettore Pedretti, Nathalie Thureau, Ming Zhao, Theo Ten Brummelaar, Harold Mcalister, Stephen T. Ridgway, Nils Turner, Judit Sturmann, Laszlo Sturmann

Information Systems and Engineering Management Research Publications

Presented are the first interferometric images of cool starspots on the chromospherically active giant λ Andromedae. Using the Michigan Infra-Red Combiner coupled to the Center for High Angular Resolution Astronomy Array, 26 interferometric observations were made between 2008 August 17 and 2011 September 24. The photometric time series acquired at Fairborn Observatory spanning 2008 September 20 to 2011 January 20 is also presented. The angular diameter and power-law limb-darkening coefficient of this star are 2.759 ± 0.050 mas and 0.229 ± 0.111, respectively. Starspot properties are obtained from both modeled and SQUEEZE reconstructed images. The images from 2010 through 2011 …

Visualizing Decision Trees And Forests Using Radial Trees, Angela Kozma

Computer Science and Information Technology Faculty

Data visualization has become a big representation of many company’s data and schedules. Now people are not using just simple bar graphs and pie charts in business meetings but utilizing other fields of study and even more complex graphs. By using multiple visualizations to display their results and projects, it is letting more outside people understand what they are working on and can lead to more viewpoints on the topic being displayed. Also, schedules for projects are now being displayed visually so the workers can see how much time each part of their project is going to take. With this …

Evolution Of Magnetic Field Induced Ordering In The Layered Quantum Heisenberg Triangular-Lattice Antiferromagnet Ba3 Cosb2 O9, Nathanael Alexander Fortune, Q. Huang, T. Hong, J. Ma, E. S. Choi, Scott T. Hannahs, Z. Y. Zhao, X. F. Sun, Y. Takano, H. D. Zhou

Physics: Faculty Publications

Quantum fluctuations in the effective spin- 1/2 layered triangular-lattice quantum Heisenberg antiferromagnet Ba₃CoSb₂O₉ lift the classical degeneracy of the antiferromagnetic ground state in magnetic field, producing a series of novel spin structures for magnetic fields applied within the crystallographic ab plane, including a celebrated collinear “up-up-down” spin ordering with magnetization equal to 1/3 of the saturation magnetization over an extended field range. Theoretically unresolved, however, are the effects of interlayer antiferromagnetic coupling and transverse magnetic fields on the ground states of this system. Additional magnetic field induced phase transitions are theoretically expected and in some …

Exercise, Cognition, And Cannabis Use In Adolescents, Ileana Pacheco-Colón

FIU Electronic Theses and Dissertations

Heavy and/or chronic cannabis use has been associated with neurocognitive impairment and decline, often in domains such as memory and executive functioning. On the other hand, exercise has been linked to positive effects on brain and cognitive health across the lifespan, as well as to better substance use outcomes. Despite this, little is known about the ways in which exercise could help prevent or ameliorate adverse cannabis-related outcomes among adolescents.

Through three separate studies, the current dissertation examines interrelations among exercise, cognition, and cannabis use in children and adolescents in an effort to determine whether exercise can prevent or ameliorate …

Replication Data For: Study Of Methane Migration In The Shallow Subsurface From A Gas Pipe Leak, Kathleen Smits

Earth & Environmental Sciences Datasets

With the increased use of natural gas, safety and environmental concerns from underground leaking natural gas pipelines are becoming more widespread. What is not well understood in leakage incidents is how the soil conditions affect gas migration behavior, making it difficult to estimate the gas distribution. To shed light on these concerns, an increased understanding of subsurface methane migration after gas release is required to support efficient leak response and effective use of available technologies. In this study, three field-scale experiments were performed at the Methane Emission Technology Evaluation Center in Colorado State University to investigate the effect of soil …

Has Excessive Violence In Video Games Gone Too Far?, Kyra Sycip

ART 108: Introduction to Games Studies

Numerous case studies and published research have led many gamers and non-gamers to wonder whether the excessive loads of violence found in video games is truly necessary for “fun” gameplay and entertainment. Controversies have been arising within famous video games such as the Grand Theft Auto series, Call Of Duty: Modern Warfare 2, and Six Days in Fallujah. These three games have been the subject of numerous present day debates and have sparked many arguments within the gaming community. As well as the debate of whether these games are indeed harmful to the player’s psychology and nature has yet to …

Sound In Video Games: How Sound Is An Important Aspect Of The Virtual Experience, James Boen

ART 108: Introduction to Games Studies

This paper will take the form of an analysis, with video games as the medium/text that will be analysed. Although analysis is typically reserved for poems, books, short stories, or plays, video games are simply a form of conveying ideas and a form of text that is representative of the 21st century. Video games is a rare medium that has an interactive element, which can alter/enhance the experience an audience member can have, even if there were the same audio/visual components in a film or play. In most forms of media with an audio component, the analysis is done by …

On Properties Of Weil Sums Of Binomials, Liem P. Nguyen

LSU Doctoral Dissertations

This dissertation explores questions regarding the Weil sum of binomials, a finite field character sum originated from information theory. The Weil spectrum counts distinct values of the Weil sum through invertible elements in the finite field. The value of these sums and the size of the Weil spectrum are of particular interest, as they link problems in information theory, coding theory, and cryptography to other areas of math such as number theory and arithmetic geometry. In the setting of Niho exponents, we prove the Vanishing Conjecture of Helleseth ($1971$) on the presence of zero values in the Weil spectrum and …

Binding Affinity Of Flavins To The Dehydrogenase Domain Of Spnox, Quinesha Williams

Master of Science in Chemical Sciences Theses

NADPH oxidases (NOX’s) are enzymes that catalyze the production of superoxide through single electron transfer. This superoxide production leads to the production of other reactive oxygen species (ROS). ROS affect many metabolic processes throughout the body that can cause several different diseases, making this an ideal target for drug discovery. The general structure of NOX contains a transmembrane (TM) domain and a dehydrogenase (DH) domain connected by a linker. The DH domain contains binding sites for FAD and NADPH/NADH that both participate in the electron transfer necessary for producing superoxide. Structural information of NOX’s is still relatively new to the …

Translating Natural Language Queries To Sparql, Shreya Satish Bhajikhaye

Master's Projects

The Semantic Web is an extensive knowledge base that contains facts in the form of RDF
triples. These facts are not easily accessible to the average user because to use them requires
an understanding of ontologies and a query language like SPARQL. Question answering systems
form a layer of abstraction on linked data to overcome these issues. These systems allow the
user to input a question in a natural language and receive the equivalent SPARQL query. The
user can then execute the query on the database to fetch the desired results. The standard
techniques involved in translating natural language questions …

Detecting And Predicting Visual Affordance Of Objects In A Given Environment, Bhumika Kaur Matharu

Master's Projects

The rapid growth of the development of autonomous robots is transforming the manufacturing and healthcare industry in many ways, but they still face many challenges. One of the challenges experienced by autonomous robots is their inability to manipulate an unknown object without human supervision. One way through which autonomous robots can manipulate an unknown object is affordance learning [1]. Affordance describes the action a user can perform on the object in given surroundings. This report describes our proposed model to detect and predict the affordance of an object from videos by leveraging the spatial-temporal feature extraction through ConvLSTM and Fully …