Physical Sciences and Mathematics Commons^™

Clustering Web Concepts Using Algebraic Topology, Harleen Kaur Ahuja

Master's Projects

In this world of Internet, there is a rapid amount of growth in data both in terms of size and dimension. It consists of web pages that represents human thoughts. These thoughts involves concepts and associations which we can capture. Using mathematics, we can perform meaningful clustering of these pages. This project aims at providing a new problem solving paradigm known as algebraic topology in data science. Professor Vasant Dhar, Editor-In-Chief of Big Data (Professor at NYU) define data science as a generalizable extraction of knowledge from data. The core concept of semantic based search engine project developed by my …

Predicting 'Attention Deficit Hyperactive Disorder' Using Large Scale Child Data Set, Arpi Shah

Master's Projects

Attention deficit hyperactivity disorder (ADHD) is a disorder found in children affecting about 9.5% of American children aged 13 years or more. Every year, the number of children diagnosed with ADHD is increasing. There is no single test that can diagnose ADHD. In fact, a health practitioner has to analyze the behavior of the child to determine if the child has ADHD. He has to gather information about the child, and his/her behavior and environment. Because of all these problems in diagnosis, I propose to use Machine Learning techniques to predict ADHD by using large scale child data set. Machine …

Entity And Relational Queries Over Big Data Storage, Nachappa Achakalera Ponnappa

Master's Projects

Big data storage involves using NoSQL technologies to handle and process huge volumes of data. NoSQL databases are non-relational, schema-free where data is stored as key-value pairs. The aim of the thesis is to implement Entity and Relational queries on top of Big Data storage. In order to achieve this, we use NoSQL technologies like MongoDB and HBase. We implement various methodologies and solutions on top of MongoDB and HBase to map data across different tables and implement entity and relational queries to retrieve entities from huge volumes of data. We also measure the performance of both the technologies and …

Predicting Autism Over Large-Scale Child Dataset, Arpit Arya

Master's Projects

Data Analytics and Machine learning in healthcare are one of the most emerging and needed fields in current time. Also, a lot of research has been performed and is still being done in this field. In healthcare, gone are those days when only doctor examines and patient listens. Now doctor has a lot of technologies which can assist him and help in accurately diagnosing the disease with which his patient is suffering. The backbone of such technologies is data analytics and machine learning where we can make out a lot of inferences from tons of patients‟ data already available. This …

Load Balancing For Entity Matching Over Big Data Using Sorted Neighborhood, Yogesh Wattamwar

Master's Projects

Entity matching also known as entity resolution, duplicate identification, reference reconciliation or record linkage and is a critically important task for data cleaning and data integration. One can think of it, as the task of finding entities matching to the same entity in the real world. These entities can belong to a single source of data, or distributed data-sources. It takes structured data as an input and process includes comparison of that structured data (entity or database record) with entities present in the knowledge base. For large-scale entity, matching data has to go through some sequence of steps, which includes …

Relationship Based Entity Recommendation System, Rakhi Poonam Verma

Master's Projects

With the increase in usage of the internet as a place to search for information, the importance of the level of relevance of the results returned by search engines have increased by many folds in recent years. In this paper, we propose techniques to improve the relevance of results shown by a search engine, by using the kinds of relationships between entities a user is interested in. We propose a technique that uses relationships between entities to recommend related entities from a knowledge base which is a collection of entities and the relationships with which they are connected to other …

Graph Basesd Word Sense Disambiguation For Clinical Abbreviations Using Apache Spark, Veebha Padavkar

Master's Projects

Identification of the correct sense for an ambiguous word is one of the major challenges for language processing in all domains. Word Sense Disambiguation is the task of identifying the correct sense of an ambiguous word by referencing the surrounding context of the word. Similar to the narrative documents, clinical documents suffer from ambiguity issues that impact automatic extraction of correct sense from the document. In this project, we propose a graph-based solution based on an algorithm originally implemented by Osmar R. Zaine et al. for word sense disambiguation specifically focusing on clinical text. The algorithm makes use of proposed …

A Recommendation Engine Using Apache Spark, Swapna Kulkarni

Master's Projects

The volume of structured and unstructured data has grown at exponential scale in recent days. As a result of this rapid data growth, we are always inundated with plethora of choices in any product or service. It is very natural to get lost in the amazon of such choices and finding hard to make decisions. The project aims at addressing this problem by using entity recommendation. The two main aspects that the project concentrates on are implementing and presenting more accurate entity recommendations to the user and another is dealing with vast amount of data. The project aims at presenting …

Study Of Big Data Arhitecture Lambda Arhitecture, Jaideep Katkar

Master's Projects

The lambda architecture introduced by Marz is generic, scalable and fault-tolerant data processing architecture. It aims to satisfy the needs for a robust system that is faulttolerant, both against hardware failures and human mistakes, being able to serve a wide range of workloads and use cases. The architecture proposal decomposes the problem into three layers: a) the batch layer focuses on fault tolerance and optimizes for precise results b) the speed layer is optimized for short response-times and only takes into account the most recent data and c) the serving layer provides low latency views to the results of the …

Designing A Programming Contract Library For Java, Neha Rajkumar

Master's Projects

Programmers are now developing large and complex software systems, so it’s important to have software that is consistent, efficient, and robust. Programming contracts allow developers to specify preconditions, postconditions, and invariants in order to more easily identify programming errors. The design by contract principle [1] was first used in the Eiffel programming language [2], and has since been extended to libraries in many other languages. The purpose of my project is to design a programming contract library for Java. The library supports a set of preconditions, postconditions, and invariants that are specified in Java annotations. It incorporates contract checking for …

Author Recognition Using Locality Sensitive Hashing & Alergia (Stochastic Finite Automata), Prashanth Sandela

Master's Projects

In today’s world data grows very fast. It is difficult to answer questions like 1) Is the content completely written by this author, 2) Did he get few sentences or pages from another author, 3) Is there any way to identify actual author. There are many plagiarism software’s available in the market which identify duplicate content. It doesn’t understand writing pattern involved. There is always a necessity to make an effort to find the original author. Locality sensitive hashing is one such standard for applying hashing to recognize authors writing pattern.

Extensible Authentication Protocol Vulnerabilities And Improvements, Akshay Baheti

Master's Projects

Extensible Authentication Protocol(EAP) is a widely used security protocol for Wireless networks around the world. The project examines different security issues with the EAP based protocols, the family of security protocols for Wireless LAN. The project discovers an attack on the subscriber identity module(SIM) based extension of EAP. The attack is a Denial-of-Service attack that exploits the error handling mechanism in EAP protocols. The project further proposes countermeasures for detection and a defense against the discovered attack. The discovered attack can be prevented by changing the protocol to delay the processing of protocol error messages.

The Sluggs Survey: Globular Cluster Kinematics In A ‘Double Sigma’ Galaxy – Ngc 4473, Adebusola Alabi, Caroline Foster, Duncan Forbes, Aaron Romanowsky, Nicola Pastorello, Jean Brodie, Lee Spitler, Jay Strader, Christopher Usher

Faculty Publications

NGC 4473 is a so-called double sigma (2σ) galaxy, i.e. a galaxy with rare, double peaks in its 2D stellar velocity dispersion. Here, we present the globular cluster (GC) kinematics in NGC 4473 out to ∼10Re (effective radii) using data from combined Hubble Space Telescope/Advanced Camera for Surveys and Subaru/Suprime-Cam imaging and Keck/Deep Imaging Multi-Object Spectrograph. We find that the 2σ nature of NGC 4473 persists up to 3Re, though it becomes misaligned to the photometric major axis. We also observe a significant offset between the stellar and GC rotation amplitudes. This offset can be understood as a co-addition of …

The Sluggs Survey: Inferring The Formation Epochs Of Metal-Poor And Metal-Rich Globular Clusters, Duncan Forbes, Nicola Pastorello, Aaron Romanowsky, Christopher Usher, Jean Brodie, Jay Strader

Faculty Publications

We present a novel, observationally-based framework for the formation epochs and sites of globular clusters (GCs) in a cosmological context. Measuring directly the mean ages of the metal-poor and metal-rich GC subpopulations in our own Galaxy, and in other galaxies, is observationally challenging. Here we apply an alternative approach utilizing the property that the galaxy mass–metallicity relation is a strong function of redshift (or look-back age) but is relatively insensitive to galaxy mass for massive galaxies. Assuming that GCs follow galaxy mass–metallicity relations that evolve with redshift, one can estimate the mean formation epochs of the two GC subpopulations by …

Vegas: A Vst Early-Type Galaxy Survey: I. Presentation, Wide-Field Surface Photometry, And Substructures In Ngc 4472, Massimo Capaccioli, Marilena Spavone, Aniello Grado, Enrichetta Iodice, Luca Limatola, Nicola Napolitano, Michele Cantiello, Maurizio Paolillo, Aaron Romanowsky, Duncan Forbes, Thomas Puzia, Gabriella Raimondo, Pietro Schipani

Faculty Publications

Context. We present the VST Early-type GAlaxy Survey (VEGAS), which is designed to obtain deep multiband photometry in g,r,i, of about one hundred nearby galaxies down to 27.3, 26.8, and 26 mag/arcsec2 respectively, using the ESO facility VST/OmegaCAM.Aims. The goals of the survey are 1) to map the light distribution up to ten effective radii, re; 2) to trace color gradients and surface brightness fluctuation gradients out to a few re for stellar population characterization; and 3) to obtain a full census of the satellite systems (globular clusters and dwarf galaxies) out to 20% of the galaxy virial radius. The …

Vimos Mosaic Integral-Field Spectroscopy Of The Bulge And Disc Of The Early-Type Galaxy Ngc 4697, C. Spiniello, N. Napolitano, L. Coccato, V. Pota, Aaron Romanowsky, C. Tortora, G. Covone, M. Capaccioli

Faculty Publications

No abstract provided.

The Sluggs Survey: Combining Stellar And Globular Cluster Metallicities In The Outer Regions Of Early-Type Galaxies, Nicola Pastorello, Duncan Forbes, Christopher Usher, Jean Brodie, Aaron Romanowsky, Jay Strader, Lee Spitler, Adebusola Alabi, Caroline Foster, Zachary Jennings, Sreeja Kartha, Vincenzo Pota

Faculty Publications

The outer halo regions of early-type galaxies carry key information about their past accretion history. However, spectroscopically probing the stellar component at such galactocentric radii is still challenging. Using the DEep Imaging Multi-Object Spectrograph on the Keck, we have been able to measure the metallicities of the stellar and globular cluster components in 12 early-type galaxies out to more than 10Re. We find similar metallicity gradients for the metal-poor and metal-rich globular cluster subpopulations, suggesting a common formation process for the two subpopulations. This is in conflict with most current theoretical predictions, where the metal-poor globular clusters are thought to …

Comparisons Of Cirrus Cloud Properties Between Polluted And Pristine Air Based On In-Situ Observations From The Nasa Attrex, Nsf Hippo And Eu Inca Campaigns, Minghui Diao, Jorgen Jensen

Faculty Publications, Meteorology and Climate Science

Cirrus clouds, covering about 30% of the Earth’s surface area, play an important role in the climate and weather systems. Cirrus cloud radiative forcing (cooling or warming) is influenced by their microphysical (e.g., ice crystal number concentration and size distribution) and macroscopic (e.g., spatial extent) properties. Currently it is still unclear how the formation of cirrus clouds and their microphysical properties are influenced by anthropogenic emissions. In this work, we use in-situ observations from three flight campaigns to compare the cirrus cloud properties between polluted and pristine regions. Our dataset includes: (1) the NASA Airborne Tropical Tropopause Experiment (ATTREX) campaign …

The Sluggs Survey: Multipopulation Dynamical Modelling Of The Elliptical Galaxy Ngc 1407 From Stars And Globular Clusters, Vincenzo Pota, Aaron Romanowsky, Jean Brodie, Jorge Peñarrubia, Duncan Forbes, Nicola Napolitano, Caroline Foster, Matthew Walker, Jay Strader, Joel Roediger

Faculty Publications

No abstract provided.

Frustrated Abc Triblock Terpolymers Morphologies, Madalyn Radlauer, Yusuke Asai, Christophe Sinturel, Marc Hillmyer

Faculty Publications, Chemistry

No abstract provided.

Investigating The Paleoecological Consequences Of Supercontinent Breakup: Sponges Clean Up In The Early Jurassic, Frank Corsetti, Kathleen Ritterbush, David Bottjer, Sarah Greene, Yadira Ibarra, Joyce Yager, A. Joshua West, William Berelson, Silvia Rosas, Thorsten Becker, Naomi Levine, Sean Loyd, Rowan Martindale, Victoria Petryshyn, Nathan Carroll, Elizabeth Petsios, Olivia Piazza, Carlie Pietsch, Jessica Stellmann, Jeffrey Thompson, Kirstin Washington, Dylan Wilmeth

Faculty Publications

The continued release of fossil fuel carbon into the atmosphere today means it is imperative to understand Earth system response to CO2 rise, and the geologic record offers unique opportunities to investigate such behavior. Stomatal and paleosol proxies demonstrate a large change in atmospheric pCO2 across the Triassic-Jurassic (T-J) transition, concomitant with the eruption and emplacement of the Central Atlantic Magmatic Province (CAMP) and the splitting of Pangea. As one of the “big 5” mass extinctions—when the so-called modern fauna was particularly hard hit—we know the biosphere was severely affected during this time, but the details are relatively poorly understood, …

A Sluggs And Gemini/Gmos Combined Study Of The Elliptical Galaxy M60: Wide-Field Photometry And Kinematics Of The Globular Cluster System, Vincenzo Pota, Jean Brodie, Terry Bridges, Jay Strader, Aaron Romanowsky, Alexa Villaume, Zach Jennings, Favio Faifer, Nicola Pastorello, Duncan Forbes, Ainsley Campbell, Christopher Usher, Caroline Foster, Lee Spitler, Nelson Caldwell, Juan Forte, Mark Norris, Stephen Zepf, Michael Beasley, Karl Gebhardt, David Hanes, Ray Sharples, Jacob Arnold

Faculty Publications

We present new wide-field photometry and spectroscopy of the globular clusters (GCs) around NGC 4649 (M60), the third brightest galaxy in the Virgo cluster. Imaging of NGC 4649 was assembled from a recently obtained Hubble Space Telescope/Advanced Camera for Surveys mosaic, and new Subaru/Suprime-Cam and archival Canada–France–Hawaii Telescope/MegaCam data. About 1200 sources were followed up spectroscopically using combined observations from three multi-object spectrographs: Keck/Deep Imaging Multi-Object Spectrograph, Gemini/Gemini Multi-Object Spectrograph and Multiple Mirror Telescope/Hectospec. We confirm 431 unique GCs belonging to NGC 4649, a factor of 3.5 larger than previous data sets and with a factor of 3 improvement in …

Distributions Of Ice Supersaturation And Ice Crystals From Airborne Observations In Relation To Upper Tropospheric Dynamical Boundaries, Minghui Diao, Jorgen Jensen, Laura Pan, Cameron Homeyer, Shawn Honomichl, James Bresch, Aaron Bansemer

Faculty Publications, Meteorology and Climate Science

Ice supersaturation (ISS) is the prerequisite condition for cirrus cloud formation. To examine multiscale dynamics' influences on ISS formation, we analyze in situ aircraft observations (~200 m scale) over North America in coordinates relative to dynamical boundaries in the upper troposphere and lower stratosphere. Two case studies demonstrate that ISS formation is likely influenced by mesoscale uplifting, small-scale waves, and turbulence. A collective analysis of 15 flights in April–June 2008 shows that the top layers of ISS and ice crystal distributions are strongly associated with thermal tropopause height. In addition, the average occurrence frequencies of ISS and ice crystals on …

Mining Concept In Big Data, Jingjing Yang

Master's Projects

To fruitful using big data, data mining is necessary. There are two well-known methods, one is based on apriori principle, and the other one is based on FP-tree. In this project we explore a new approach that is based on simplicial complex, which is a combinatorial form of polyhedron used in algebraic topology. Our approach, similar to FP-tree, is top down, at the same time, it is based on apriori principle in geometric form, called closed condition in simplicial complex. Our method is almost 300 times faster than FP-growth on a real world database using a SJSU laptop. The database …

Cryptanalysis Of Classic Ciphers Using Hidden Markov Models, Rohit Vobbilisetty

Master's Projects

Cryptanalysis is the study of identifying weaknesses in the implementation of cryptographic algorithms. This process would improve the complexity of such algo- rithms, making the system secure.

In this research, we apply Hidden Markov Models (HMMs) to classic cryptanaly- sis problems. We show that with sufficient ciphertext, an HMM can be used to break a simple substitution cipher. We also show that when limited ciphertext is avail- able, using multiple random restarts for the HMM increases our chance of successful decryption.

Adding Syntax Parameters To The Sweet.Js Macro Library For Javascript, Vimal Kumar

Master's Projects

Lisp and Scheme have demonstrated the power of macros to enable programmers to evolve and craft languages. A macro is a rule or pattern that specifies how a certain input sequence should be mapped to an output sequence according to some defined procedure. Using a macro system a programmer can introduce new syntactic elements to the programming language. Macros found in a program are expanded by a macro expander and allow a programmer to enable code reuse. Mozilla Sweet.JS provides a way for developers to enrich their JavaScript code by adding new syntax to the language through the use of …

Introducing Faceted Exception Handling For Dynamic Information Flow, Sri Tej Narala

Master's Projects

JavaScript is most commonly used as a part of web browsers, especially client- side scripts interacting with the user. JavaScript is also the source of many security problems, which includes cross-site scripting attacks. The primary challenge is that code from untrusted sources run with full privileges on the client side, thus lead- ing to security breaches. This paper develops information flow controls with proper exception handling to prevent violations of data confidentiality and integrity.

Faceted values are a mechanism to handle dynamic information flow security in a way that overcomes the limitations caused by dynamic execution, but previous work has …

Support Vector Machines And Metamorphic Malware Detection, Tanuvir Singh

Master's Projects

Metamorphic malware changes its internal structure with each infection, which makes it challenging to detect. In this research, we test several scor- ing techniques that have shown promise in metamorphic detection. We then perform a careful robustness analysis by employing morphing strategies that cause each score to fail. Finally, we show that combining scores using a Sup- port Vector Machine (SVM) yields results that are significantly more robust than we obtained using any of the individual scores.

Clustering Versus Svm For Malware Detection, Usha Narra

Master's Projects

Previous work has shown that we can effectively cluster certain classes of mal- ware into their respective families. In this research, we extend this previous work to the problem of developing an automated malware detection system. We first compute clusters for a collection of malware families. Then we analyze the effectiveness of clas- sifying new samples based on these existing clusters. We compare results obtained using �-means and Expectation Maximization (EM) clustering to those obtained us- ing Support Vector Machines (SVM). Using clustering, we are able to detect some malware families with an accuracy comparable to that of SVMs. One …

Optimization Of Scheduling And Dispatching Cars On Demand, Vu Tran

Master's Projects

Taxicab is the most common type of on-demand transportation service in the city because its dispatching system offers better services in terms of shorter wait time. However, the shorter wait time and travel time for multiple passengers and destinations are very considerable. There are recent companies implemented the real-time ridesharing model that expects to reduce the riding cost when passengers are willing to share their rides with the others. This model does not solve the shorter wait time and travel time when there are multiple passengers and destinations. This paper investigates how the ridesharing can be improved by using the …