Computer Sciences Commons^™

Toward On-Demand Profile Hidden Markov Models For Genetic Barcode Identification, Jessica Sheu

Master's Projects

Genetic identification aims to solve the shortcomings of morphological identification. By using the cytochrome c oxidase subunit 1 (COI) gene as the Eukaryotic “barcode,” scientists hope to research species that may be morphologically ambiguous, elusive, or similarly difficult to visually identify. Current COI databases allow users to search only for existing database records. However, as the number of sequenced, potential COI genes increases, COI identification tools should ideally also be informative of novel, previously unreported sequences that may represent new species. If an unknown COI sequence does not represent a reported organism, an ideal identification tool would report taxonomic ranks …

Declassification Of Faceted Values In Javascript, Shreya Gangishetty

Master's Projects

This research addresses the issues with protecting sensitive information at the language level using information flow control mechanisms (IFC). Most of the IFC mechanisms face the challenge of releasing sensitive information in a restricted or limited manner. This research uses faceted values, an IFC mechanism that has shown promising flexibility for downgrading the confidential information in a secure manner, also called declassification.

In this project, we introduce the concept of first-class labels to simplify the declassification of faceted values. To validate the utility of our approach we show how the combination of faceted values and first-class labels can build various …

Predictive Analysis For Cloud Infrastructure Metrics, Paridhi Agrawal

Master's Projects

In a cloud computing environment, enterprises have the flexibility to request resources according to their application demands. This elastic feature of cloud computing makes it an attractive option for enterprises to host their applications on the cloud. Cloud providers usually exploit this elasticity by auto-scaling the application resources for quality assurance. However, there is a setup-time delay that may take minutes between the demand for a new resource and it being prepared for utilization. This causes the static resource provisioning techniques, which request allocation of a new resource only when the application breaches a specific threshold, to be slow and …

Assessing Code Obfuscation Of Metamorphic Javascript, Kaushik Murli

Master's Projects

Metamorphic malware is one of the biggest and most ubiquitous threats in the digital world. It can be used to morph the structure of the target code without changing the underlying functionality of the code, thus making it very difficult to detect using signature-based detection and heuristic analysis. The focus of this project is to analyze Metamorphic JavaScript malware and techniques that can be used to mutate the code in JavaScript. To assess the capabilities of the metamorphic engine, we performed experiments to visualize the degree of code morphing. Further, this project discusses potential methods that have been used to …

Species Classification Using Dna Barcoding And Profile Hidden Markov Models, Sphoorti Poojary

Master's Projects

Traditional classification systems for living organisms like the Linnaean taxonomy involved classification based on morphological features of species. This traditional system is being replaced by molecular approaches which involve using gene sequences. The COI gene, also known as the ”DNA barcode” since it is unique in every species, can be used to uniquely identify organisms and thus, classify them. Classifying using gene sequences has many advantages, including correct identification of cryptic species(individuals which appear similar but belong to different species) and species which are extremely small in size. In this project, I worked on classifying COI sequences of unknown species …

Image Compression Using Neural Networks, Kunal Rajan Deshmukh

Master's Projects

Image compression is a well-studied field of Computer Vision. Recently, many neural network based architectures have been proposed for image compression as well as enhancement. These networks are also put to use by frameworks such as end-to-end image compression.

In this project, we have explored the improvements that can be made over this framework to achieve better benchmarks in compressing images. Generative Adversarial Networks are used to generate new fake images which are very similar to original images. Single Image Super-Resolution Generative Adversarial Networks

(SI-SRGAN) can be employed to improve image quality. Our proposed architecture can be divided into four …

Nitrogenase Iron Protein Detection Using Neural Network, Ishan Shinde

Master's Projects

Nitrogenase Iron Protein (nifH) is the enzyme responsible for nitrogen fixation. Microbes with nifH gene are responsible for injecting reduced nitrogen into the biosphere, which is essential for all living things. Obtaining sequences from GenBank database is problematic due to annotation errors, nomenclature variation and paralogues. One possible solution could be to retrieve sequences from the GenBank database and use a sequence classifier to label the sequences. In this research, we convert sequences to images and build a nifH sequence classifier using image processing and convolutional neural network. We built a nifH classification model which can classify sequences with an …

Proposing An Optimized Algorithm For Consolidating Electric-Powered Shared Scooters Into Hubs For Efficiently Managing Their Charging And Maintenance Operations, Ojen Goshtasb

Master's Projects

The use of vehicles other than ones containing combustion engines have been adopted significantly over the past few years and the direction it’s taking seems to be the future of urban transportation. The hottest vehicle of choice currently is the electric scooter. They are small and portable, fast, and less costly compared to getting in a cab from Lyft or Uber to get around town. The goal of this paper is to make a proposal to drive the creation of a safe, efficient system for these scooters’ management. This must be beneficial to all parties involved; the rider, non-riders, and …

Management And Security Of Iot Systems Using Microservices, Tharun Theja Kammara

Master's Projects

Devices that assist the user with some task or help them to make an informed decision are called smart devices. A network of such devices connected to internet are collectively called as Internet of Things (IoT). The applications of IoT are expanding exponentially and are becoming a part of our day to day lives. The rise of IoT led to new security and management issues. In this project, we propose a solution for some major problems faced by the IoT devices, including the problem of complexity due to heterogeneous platforms and the lack of IoT device monitoring for security and …

Virtual Robot Climbing Using Reinforcement Learning, Ujjawal Garg

Master's Projects

Reinforcement Learning (RL) is a field of Artificial Intelligence that has gained a lot of attention in recent years. In this project, RL research was used to design and train an agent to climb and navigate through an environment with slopes. We compared and evaluated the performance of two state-of-the-art reinforcement learning algorithms for locomotion related tasks, Deep Deterministic Policy Gradients (DDPG) and Trust Region Policy Optimisation (TRPO). We observed that, on an average, training with TRPO was three times faster than DDPG, and also much more stable for the locomotion control tasks that we experimented. We conducted experiments and …

Deep Visual Recommendation System, Raksha Sunil

Master's Projects

Recommendation system is a filtering system that predicts ratings or preferences that a user might have. Recommendation system is an evolved form of our trivial information retrieval systems. In this paper, we present a technique to solve new item cold start problem. New item cold start problem occurs when a new item is added to a shopping website like Amazon.com. There is no metadata for this item, no ratings and no reviews because it’s a new item in the system. Absence of data results in no recommendation or bad recommendations. Our approach to solve new item cold start problem requires …

Pantry: A Macro Library For Python, Derek Pang

Master's Projects

Python lacks a simple way to create custom syntax and constructs that goes outside of its own syntax rules. A paradigm that allows for these possibilities to exist within languages is macros. Macros allow for a shorter set of syntax to expand into a longer set of instructions at compile-time. This gives the capability to evolve the language to fit personal needs.

Pantry, implements a hygienic text-substitution macro system for Python. Pantry achieves this through the introduction of an additional preparsing step that utilizes parsing and lexing of the source code. Pantry proposes a way to simply declare a pattern …

Variations On A Theme: Using Amino Acid Sequences To Generate Music, Aaron Kosmatin

Master's Projects

In this project, we explore using a musical space to represent the properties of amino acids. We consider previous mappings and explore the limitations of these mappings. In this exploration, we will propose a new method of mapping into musical spaces that extends the properties that can be represented. For this work, we will use amino acid sequences as our example mapping. The amino acid properties we will use include mass, charge, structure, and hydrophobicity. Finally, we will show how the different musical properties can be compared for similarity.

Intra-Exchange Cryptocurrency Arbitrage Bot, Eric Han

Master's Projects

Cryptocurrencies are defined as a digital currency in which encryption techniques are utilized to regulate generation of units of currency and verify the transfer of funds, independent of a central governing body such as a bank. Due to the large number of cryptocurrencies currently available, there inherently exists many price discrepancies due to market inefficiencies. Market inefficiencies occur when the price of assets do not reflect their true value. In fact, these types of pricing discrepancies exist in other financial markets, including fiat currency exchanges and stock exchanges. However, these discrepancies are more significant in the cryptocurrency domain due to …

Gradubique: An Academic Transcript Database Using Blockchain Architecture, Thinh Nguyen

Master's Projects

Blockchain has been widely adopted in the last few years even though it is in its infancy. The first well-known application built on blockchain technology was Bitcoin, which is a decentralized and distributed ledger to record crypto-currency transactions. All of the transactions in Bitcoin are anonymously transferred and validated by participants in the network. Bitcoin protocol and its operations are so reliable that technologists have been inspired to enhance blockchain technologies and deploy it outside of the crypto-currency world. The demand for private and non-crypto-currency solutions have surged among consortiums because of the security and fault tolerant features of blockchain. …

Dynamic Hierarchical Cache Management For Cloud Ran And Multi- Access Edge Computing In 5g Networks, Deepika Pathinga Rajendiran

Master's Projects

Cloud Radio Access Networks (CRAN) and Multi-Access Edge Computing (MEC) are two of the many emerging technologies that are proposed for 5G mobile networks. CRAN provides scalability, flexibility, and better resource utilization to support the dramatic increase of Internet of Things (IoT) and mobile devices. MEC aims to provide low latency, high bandwidth and real- time access to radio networks. Cloud architecture is built on top of traditional Radio Access Networks (RAN) to bring the idea of CRAN and in MEC, cloud computing services are brought near users to improve the user’s experiences. A cache is added in both CRAN …

Prioritized Task Scheduling In Fog Computing, Tejaswini Choudhari

Master's Projects

Cloud computing is an environment where virtual resources are shared among the many users over network. A user of Cloud services is billed according to pay-per-use model associated with this environment. To keep this bill to a minimum, efficient resource allocation is of great importance. To handle the many requests sent to Cloud by the clients, the tasks need to be processed according to the SLAs defined by the client. The increase in the usage of Cloud services on a daily basis has introduced delays in the transmission of requests. These delays can cause clients to wait for the response …

Vgm-Rnn: Recurrent Neural Networks For Video Game Music Generation, Nicolas Mauthes

Master's Projects

The recent explosion of interest in deep neural networks has affected and in some cases reinvigorated work in fields as diverse as natural language processing, image recognition, speech recognition and many more. For sequence learning tasks, recurrent neural networks and in particular LSTM-based networks have shown promising results. Recently there has been interest – for example in the research by Google’s Magenta team – in applying so-called “language modeling” recurrent neural networks to musical tasks, including for the automatic generation of original music. In this work we demonstrate our own LSTM-based music language modeling recurrent network. We show that it …

Android De-Shredder App, Vasudha Venkatesh

Master's Projects

Sensitive documents are usually shredded into strips before discarding them. Shredders are used to cut the pages of a document into thin strips of uniform thickness. Each shredded piece in the collection bin could belong to any of the pages in a document. The task of document reconstruction involves two steps: Identifying the page to which each shred belongs and rearranging the shreds within the page to their original position. The difficulty of the reconstruction process depends on the thickness of the shred and type of cut (horizontal or vertical). The thickness of the shred is directly proportional to the …

Improved Hands-Free Text Entry System, Gaurav Gupta

Master's Projects

An input device is a hardware device which is used to send input data to a computer or which is used to control and interact with a computer system. Contemporary input mechanisms can be categorized by the input medium: Keyboards and mice are hand-operated, Siri and Alexa are voice-based, etc. The objective of this project was to come up with a head movement based input system that improves upon earlier such systems. Input entry based on head movements may help people with disabilities to interact with computers more easily. The system developed provides the flexibility to capture rigid and non- …

Approaches To Shared State In Concurrent Programs, Sidharth Mishra

Master's Projects

We are in the multicore machine era, but our programs have yet to utilize the increased computing power offered by these machines. At present, lock-based multithreaded programming is the most common programming model used for writing concurrent programs. However, due to the nuances of shared state (and memory) in multithreaded programs and the cognitive load introduced due to locks, concurrent programming remains difficult. One way to deal with shared state in concurrent programs is to get rid of it altogether and use message passing. The other way would be to isolate shared state and store it in a state store, …

Image Segmentation And Classification Of Marine Organisms, Krishna Teja Vojjila

Master's Projects

To automate the arduous task of identifying and classifying images through their domain expertise, pioneers in the field of machine learning and computer vision invented many algorithms and pre-processing techniques. The process of classification is flexible with many user and domain specific alterations. These techniques are now being used to classify marine organisms to study and monitor their populations. Despite advancements in the field of programming languages and machine learning, image segmentation and classification for unlabeled data still needs improvement. The purpose of this project is to explore the various pre-processing techniques and classification algorithms that help cluster and classify …

Distinguishing Earthquakes And Noise Using Random Forest Algorithm, Nishita Narvekar

Master's Projects

Earthquakes are a major cause of life and property destruction. It is known that earthquakes radiate energy in the form of surface and body seismic waves. P-wave and S-waves are types of body waves. Both waves can be detected and recorded at an earthquake station. These waves can be analyzed to detect earthquakes. Most of the earthquake prediction techniques today are a combination of geophysics and signal processing, which are relatively complex. Machine learning can be used to learn the behavior of seismic waves and help in early detection. Machine learning can also be employed to process massive amounts of …

Agent-Based Computing In Java, Michael Symonds

Master's Projects

Agents are powerful, autonomous entities capable of performing simple, or vastly complex, operations individually or in groups of agent systems. Their capabilities extend significantly as mobile agents distributed across a network. Agent-based computing is a widely used technology with a broad range of applications, particularly in distributed computing and agent-based modeling. Many types of systems can be designed using the different architectures that define how they act, communicate, migrate, and more. This paper surveys agent-based computing, their architectures, and efforts at the standardization of certain aspects of the technology. It explores an existing framework called Jade through the lens of …

Music Similarity Estimation, Anusha Sridharan

Master's Projects

Music is a complicated form of communication, where creators and culture communicate and expose their individuality. After music digitalization took place, recommendation systems and other online services have become indispensable in the field of Music Information Retrieval (MIR). To build these systems and recommend the right choice of song to the user, classification of songs is required. In this paper, we propose an approach for finding similarity between music based on mid-level attributes like pitch, midi value corresponding to pitch, interval, contour and duration and applying text based classification techniques. Our system predicts jazz, metal and ragtime for western music. …

Micro-Expression Recognition Using Spatiotemporal Texture Map And Motion Magnification, Shashank Shivaji Pawar

Master's Projects

Micro-expressions are short-lived, rapid facial expressions that are exhibited by individuals when they are in high stakes situations. Studying these micro-expressions is important as these cannot be modified by an individual and hence offer us a peek into what the individual is actually feeling and thinking as opposed to what he/she is trying to portray. The spotting and recognition of micro-expressions has applications in the fields of criminal investigation, psychotherapy, education etc. However due to micro-expressions’ short-lived and rapid nature; spotting, recognizing and classifying them is a major challenge. In this paper, we design a hybrid approach for spotting and …

Fine-Grained Object Detection, Rahul Dalal

Master's Projects

Object detection plays a vital role in many real-world computer vision applications such as selfdriving cars, human-less stores and general purpose robotic systems. Convolutional Neural Network(CNN) based Deep Learning has evolved to become the backbone of most computer vision algorithms, including object detection. Most of the research has focused on detecting objects that differ significantly e.g. a car, a person, and a bird. Achieving fine-grained object detection to detect different types within one class of objects from general object detection can be the next step. Fine-grained object detection is crucial to tasks like automated retail checkout. This research has developed …

Using Filters In Time-Based Movie Recommender Systems, Ravee Khandagale

Master's Projects

On a very high level, a movie recommendation system is one which uses data about the user, data about the movie and the ratings given by a user in order to generate predictions for the movies that the user will like. This prediction is further presented to the user as a recommendation. For example, Netflix uses a recommendation system to predict movies and generate favorable recommendations for users based on their profiles and the profiles of users similar to them. In user-based collaborative filtering algorithm, the movies rated highly by the similar users of a particular user are considered as …

Compression Of Wearable Body Sensor Network Data Using Improved Two-Threshold-Two-Divisor Data Chunking Algorithm, Robinson Raju

Master's Projects

Compression plays a significant role in Body Sensor Networks (BSN) data since the sensors in BSNs have limited battery power and memory. Also, data needs to be transmitted fast and in a lossless manner to provide near real-time feedback. The paper evaluates lossless data compression algorithms like Run Length Encoding (RLE), Lempel Zev Welch (LZW) and Huffman on data from wearable devices and compares them in terms of Compression Ratio, Compression Factor, Savings Percentage and Compression Time. It also evaluates a data deduplication technique used for Low Bandwidth File Systems (LBFS) named Two Thresholds Two Divisors (TTTD) algorithm to determine …

A Medical Price Prediction System, Anuja Tike

Master's Projects

The health care costs constitute a significant fraction of the U.S. economy. Nearly 20% of the Gross Domestic Product (GDP) is spent on health care. The health spending in the US is the highest among all developed nations in absolute numbers as well as a percentage of the economy. The U.S. government bears a large portion of seniors’ health expenditure through its Medicare program. The growing health related expenses combined with the fact that the baby-boomer generation is retiring, and hence they will be eligible for Medicare, puts a great burden on the U.S. exchequer. Therefore, it is essential to …