Physical Sciences and Mathematics Commons^™

Breadcrumbs: Privacy As A Privilege, Prachi Bhardwaj

Capstones

Breadcrumbs: Privacy as a Privilege Abstract

By: Prachi Bhardwaj

In 2017, the world saw more data breaches than in any year prior. The count was more than the all-time high record in 2016, which was 40 percent more than the year before that.

That’s because consumer data is incredibly valuable today. In the last three decades, data storage has gone from being stored physically to being stored almost entirely digitally, which means consumer data is more accessible and applicable to business strategies. As a result, companies are gathering data in ways previously unknown to the average consumer, and hackers are …

Real-Time Indoor Assistive Localization With Mobile Omnidirectional Vision And Cloud Gpu Acceleration, Feng Hu, Zhigang Zhu, Jeury Mejia, Hao Tang

Publications and Research

In this paper we propose a real-time assistive localization approach to help blind and visually impaired people in navigating an indoor environment. The system consists of a mobile vision front end with a portable panoramic lens mounted on a smart phone, and a remote image feature-based database of the scene on a GPU-enabled server. Compact and elective omnidirectional image features are extracted and represented in the smart phone front end, and then transmitted to the server in the cloud. These features of a short video clip are used to search the database of the indoor environment via image-based indexing to …

Ethics And Bias In Machine Learning: A Technical Study Of What Makes Us “Good”, Ashley Nicole Shadowen

Student Theses

The topic of machine ethics is growing in recognition and energy, but bias in machine learning algorithms outpaces it to date. Bias is a complicated term with good and bad connotations in the field of algorithmic prediction making. Especially in circumstances with legal and ethical consequences, we must study the results of these machines to ensure fairness. This paper attempts to address ethics at the algorithmic level of autonomous machines. There is no one solution to solving machine bias, it depends on the context of the given system and the most reasonable way to avoid biased decisions while maintaining the …

Study Of Self-Similarity In Brain Data, Jennifer Holst

Student Theses

In the area of computer science, past research has found that the concept of self-similarity is present in local and Internet-based network traffic. This study considers the possibility that data traveling through the neuronal network in the human brain is also self-similar. By analyzing publicly available raw EEG data and estimating its Hurst parameter, we find indications that brain data traffic may in fact be self-similar.

On Improvised Music, Computational Creativity And Human-Becoming, Arto Artinian, Adam James Wilson

Publications and Research

Music improvisation is an act of human-becoming: of self-expression—an articulation of histories and memories that have molded its participants—and of exploration—a search for unimagined structures that break with the stale norms of majoritarian culture. Given that the former objective may inhibit the latter, we propose an integration of human musical improvisers and deliberately flawed creative software agents that are designed to catalyze the development of human-ratified minoritarian musical structures.

Defaultification Refactoring: A Tool For Automatically Converting Java Methods To Default, Raffi T. Khatchadourian, Hidehiko Masuhara

Publications and Research

Enabling interfaces to declare (instance) method implementations, Java 8 default methods can be used as a substitute for the ubiquitous skeletal implementation software design pattern. Performing this transformation on legacy software manually, though, may be non-trivial. The refactoring requires analyzing complex type hierarchies, resolving multiple implementation inheritance issues, reconciling differences between class and interface methods, and analyzing tie-breakers (dispatch precedence) with overriding class methods. All of this is necessary to preserve type-correctness and confirm semantics preservation. We demonstrate an automated refactoring tool called Migrate Skeletal Implementation to Interface for transforming legacy Java code to use the new default construct. The …

Exploring The Internal Statistics: Single Image Super-Resolution, Completion And Captioning, Yang Xian

Dissertations, Theses, and Capstone Projects

Image enhancement has drawn increasingly attention in improving image quality or interpretability. It aims to modify images to achieve a better perception for human visual system or a more suitable representation for further analysis in a variety of applications such as medical imaging, remote sensing, and video surveillance. Based on different attributes of the given input images, enhancement tasks vary, e.g., noise removal, deblurring, resolution enhancement, prediction of missing pixels, etc. The latter two are usually referred to as image super-resolution and image inpainting (or completion).

Image super-resolution and completion are numerically ill-posed problems. Multi-frame-based approaches make use of the …

Involute Analysis: Virtual Discourse, Memory Systems And Archive In The Involutes Of Thomas De Quincey, Kimberley A. Garcia

Dissertations, Theses, and Capstone Projects

Thomas De Quincey’s involutes inform metaphysical thought on memory and language, particularly concerning multiplicity and the virtual, repetition and difference. When co-opting the mathematic and mechanic involute in Suspiria de Profundis, De Quincey generates an interdisciplinary matrix for the semiotics underpinning his philosophy of language and theory of memory and experience. Involutes entangle and reproduce. De Quincey’s involute exposes the concrete and actual through which all experience accesses the abstract or virtual. The materiality of their informatics and technics provides a literary model and theoretical precursor to a combination of archive and systems theory. The textuality of involute system(s)—both …

Approximation Algorithms For Effective Team Formation, George Rabanca

Dissertations, Theses, and Capstone Projects

This dissertation investigates the problem of creating multiple disjoint teams of maximum efficacy from a fixed set of workers. We identify three parameters which directly correlate to the team effectiveness — team expertise, team cohesion and team size — and propose efficient algorithms for optimizing each in various settings. We show that under standard assumptions the problems we explore are not optimally solvable in polynomial time, and thus we focus on developing efficient algorithms with guaranteed worst case approximation bounds. First, we investigate maximizing team expertise in a setting where each worker has different expertise for each job and each …

Secure And Efficient Delegation Of A Single And Multiple Exponentiations To A Single Malicious Server, Matluba Khodjaeva

Dissertations, Theses, and Capstone Projects

Group exponentiation is an important operation used in many cryptographic protocols, specifically public-key cryptosystems such as RSA, Diffie Hellman, ElGamal, etc. To expand the applicability of group exponentiation to computationally weaker devices, procedures were established by which to delegate this operation from a computationally weaker client to a computationally stronger server. However, solving this problem with a single, possibly malicious, server, has remained open since a formal cryptographic model was introduced by Hohenberger and Lysyanskaya in 2005. Several later attempts either failed to achieve privacy or only achieved constant security probability.

In this dissertation, we study and solve this problem …

Machine Learning Algorithms For Automated Satellite Snow And Sea Ice Detection, George Bonev

Dissertations, Theses, and Capstone Projects

The continuous mapping of snow and ice cover, particularly in the arctic and poles, are critical to understanding the earth and atmospheric science. Much of the world's sea ice and snow covers the most inhospitable places, making measurements from satellite-based remote sensors essential. Despite the wealth of data from these instruments many challenges remain. For instance, remote sensing instruments reside on-board different satellites and observe the earth at different portions of the electromagnetic spectrum with different spatial footprints. Integrating and fusing this information to make estimates of the surface is a subject of active research.

In response to these challenges, …

A Combinatorial Framework For Multiple Rna Interaction Prediction, Syed Ali Ahmed

Dissertations, Theses, and Capstone Projects

The interaction of two RNA molecules involves a complex interplay between folding and binding that warranted recent developments in RNA-RNA interaction algorithms. However, biological mechanisms in which more than two RNAs take part in an interaction also exist.

A typical algorithmic approach to such problems is to find the minimum energy structure. Often the computationally optimal solution does not represent the biologically correct structure of the interaction. In addition, different biological structures may be observed, depending on several factors. Furthermore, scoring techniques often miss critical details about dependencies within different parts of the structure, which typically leads to lower scores …

Morphogenesis And Growth Driven By Selection Of Dynamical Properties, Yuri Cantor

Dissertations, Theses, and Capstone Projects

Organisms are understood to be complex adaptive systems that evolved to thrive in hostile environments. Though widely studied, the phenomena of organism development and growth, and their relationship to organism dynamics is not well understood. Indeed, the large number of components, their interconnectivity, and complex system interactions all obscure our ability to see, describe, and understand the functioning of biological organisms.

Here we take a synthetic and computational approach to the problem, abstracting the organism as a cellular automaton. Such systems are discrete digital models of real-world environments, making them more accessible and easier to study then their physical world …

Machine Learning Approach To Retrieving Physical Variables From Remotely Sensed Data, Fazlul Shahriar

Dissertations, Theses, and Capstone Projects

Scientists from all over the world make use of remotely sensed data from hundreds of satellites to better understand the Earth. However, physical measurements from an instrument is sometimes missing either because the instrument hasn't been launched yet or the design of the instrument omitted a particular spectral band. Measurements received from the instrument may also be corrupt due to malfunction in the detectors on the instrument. Fortunately, there are machine learning techniques to estimate the missing or corrupt data. Using these techniques we can make use of the available data to its full potential.

We present work on four …

Zero Textbook Cost Syllabus For Cis 3367 (Spreadsheet Applications In Business), Soniya Dsouza

Open Educational Resources

The primary focus of this course is to learn how to construct and use powerful spreadsheets for effective managerial decision-making. This course is mostly project- oriented with a dual focus on spreadsheet engineering and quantitative modeling of financial applications. Students will learn to develop powerful spreadsheet models and perform data analysis using Pivot Tables, VLookUp, Data Validation techniques and Sub Total functions. Students will also learn how to enhance spreadsheets by creating dashboards on financial data. The Visual Basic (macro) concepts will also be introduced to students. With the knowledge and hands-on experience of these concepts, students will be prepared …

Digital Anti-Forensics: An Implementation And Examination, Stephanie Dachs

Student Theses

The rise of computer use and technical adeptness by the general public in the last two decades are undeniable. With greater use comes a greater possibility for misuse, evidenced by today’s incredible number of crimes involving computers as well as the growth in severity from that of cyber hooliganism to cyber warfare. Although frequently utilized for privacy and security purposes, the vast range of anti-forensic techniques has contributed to the ability for hackers and criminals to obstruct computer forensic investigations.

Understanding how anti-forensics may alter important and relevant data on an electronic device will prove useful for the success and …

Introduction To Gis Using Open Source Software, 8th Ed, Frank Donnelly

Open Educational Resources

This tutorial was created to accompany the GIS Practicum, a day-long workshop offered by the Newman Library at Baruch College CUNY that introduces participants to geographic information systems (GIS) using the open source software QGIS. The practicum introduces GIS as a concept for envisioning information and as a tool for conducting geographic analyses and creating maps. Participants learn how to navigate a GIS interface, how to prepare layers and conduct a basic geographic analysis, and how to create thematic maps. This tutorial was written using QGIS version 2.18 "Las Palmas", a cross-platform (Windows, Mac, Linux) desktop GIS software package.

Tumor Necrosis Factor Dynamically Regulates The Mrna Stabilome In Rheumatoid Arthritis Fibroblast-Like Synoviocytes, Konstantinos Loupasakis, David Kuo, Upneet K. Sokhi, Christopher Sohn, Bethany Syracuse, Eugenia G. Giannopoulou, Sung Ho Park, Hyelim Kang, Gunnar Rätsch, Lionel B. Ivashkiv, George D. Kalliolias

Publications and Research

During rheumatoid arthritis (RA), Tumor Necrosis Factor (TNF) activates fibroblast-like synoviocytes (FLS) inducing in a temporal order a constellation of genes, which perpetuate synovial inflammation. Although the molecular mechanisms regulating TNF-induced transcription are well characterized, little is known about the impact of mRNA stability on gene expression and the impact of TNF on decay rates of mRNA transcripts in FLS. To address these issues we performed RNA sequencing and genome-wide analysis of the mRNA stabilome in RA FLS. We found that TNF induces a biphasic gene expression program: initially, the inducible transcriptome consists primarily of unstable transcripts but progressively switches …

Insights Into The Binding Mode Of Mek Type-Iii Inhibitors. A Step Towards Discovering And Designing Allosteric Kinase Inhibitors Across The Human Kinome, Zheng Zhao, Lei Xie, Philip E. Bourne

Publications and Research

Protein kinases are critical drug targets for treating a large variety of human diseases. Type- III kinase inhibitors have attracted increasing attention as highly selective therapeutics. Thus, understanding the binding mechanism of existing type-III kinase inhibitors provides useful insights into designing new type-III kinase inhibitors. In this work, we have systematically studied the binding mode of MEK-targeted type-III inhibitors using structural systems pharmacology and molecular dynamics simulation. Our studies provide detailed sequence, structure, interaction-fingerprint, pharmacophore and binding-site information on the binding characteristics of MEK type-III kinase inhibitors. We hypothesize that the helix-folding activation loop is a hallmark allosteric binding site …

Travel Mode Identification With Smartphone Sensors, Xing Su

Dissertations, Theses, and Capstone Projects

Personal trips in a modern urban society typically involve multiple travel modes. Recognizing a traveller's transportation mode is not only critical to personal context-awareness in related applications, but also essential to urban traffic operations, transportation planning, and facility design. While the state of the art in travel mode recognition mainly relies on large-scale infrastructure-based fixed sensors or on individuals' GPS devices, the emergence of the smartphone provides a promising alternative with its ever-growing computing, networking, and sensing powers. In this thesis, we propose new algorithms for travel mode identification using smartphone sensors. The prototype system is built upon the latest …

Solving Algorithmic Problems In Finitely Presented Groups Via Machine Learning, Jonathan Gryak

Dissertations, Theses, and Capstone Projects

Machine learning and pattern recognition techniques have been successfully applied to algorithmic problems in free groups. In this dissertation, we seek to extend these techniques to finitely presented non-free groups, in particular to polycyclic and metabelian groups that are of interest to non-commutative cryptography.

As a prototypical example, we utilize supervised learning methods to construct classifiers that can solve the conjugacy decision problem, i.e., determine whether or not a pair of elements from a specified group are conjugate. The accuracies of classifiers created using decision trees, random forests, and N-tuple neural network models are evaluated for several non-free groups. …

Feature Selection From Large Acoustic Feature Sets In Computational Paralinguistics, Dara Pir

Dissertations, Theses, and Capstone Projects

The burgeoning field of computational paralinguistics deals with the ways in which spoken words are uttered and attempts to recognize the states and traits of the speakers. Many areas of current scientific research, including computational paralinguistics, have started to employ datasets with ever increasing number of features. Using large feature sets has helped improve recognition performances. However, processing these large sets has given rise to various problems. Feature selection methods, which reduce the dimensionality of the original feature sets by removing irrelevant and/or redundant features, could be used to address these problems.

The two main methods for feature selection are …

Sliding Window Based Feature Extraction And Traffic Clustering For Green Mobile Cyberphysical Systems, Jiao Zhang, Li Zhou, Angran Xiao, Sai Zeng, Haitao Zhao, Jibo Wei

Publications and Research

Both the densification of small base stations and the diversity of user activities bring huge challenges for today’s heterogeneous networks, either heavy burdens on base stations or serious energy waste. In order to ensure coverage of the network while reducing the total energy consumption, we adopt a green mobile cyberphysical system (MCPS) to handle this problem. In this paper, we propose a feature extractionmethod using sliding window to extract the distribution feature of mobile user equipment (UE), and a case study is presented to demonstrate that the method is efficacious in reserving the clustering distribution feature. Furthermore, we present traffic …

Automated Refactoring Of Legacy Java Software To Default Methods, Raffi T. Khatchadourian, Hidehiko Masuhara

Publications and Research

Java 8 default methods, which allow interfaces to contain (instance) method implementations, are useful for the skeletal implementation software design pattern. However, it is not easy to transform existing software to exploit default methods as it requires analyzing complex type hierarchies, resolving multiple implementation inheritance issues, reconciling differences between class and interface methods, and analyzing tie-breakers (dispatch precedence) with overriding class methods to preserve type-correctness and confirm semantics preservation. In this paper, we present an efficient, fully-automated, type constraint-based refactoring approach that assists developers in taking advantage of enhanced interfaces for their legacy Java software. The approach features an extensive …

Automated Refactoring Of Legacy Java Software To Default Methods, Raffi T. Khatchadourian, Hidehiko Masuhara

Publications and Research

Java 8 introduces enhanced interfaces, allowing for default (instance) methods that implementers will inherit if none are provided [3]. Default methods can be used [2] as a replacement of the skeletal implementation pattern [1], which creates abstract skeletal implementation classes that implementers extend. Migrating legacy code using the skeletal implementation pattern to instead use default methods can require significant manual effort due to subtle language and semantic restrictions. It requires preserving typecorrectness by analyzing complex type hierarchies, resolving issues arising from multiple inheritance, reconciling differences between class and interface methods, and ensuring tie-breakers with overriding class methods do not alter …

Toward Measuring Network Aesthetics Based On Symmetry, Zengqiang Chen, Matthias Dehmer, Frank Emmert-Streib, Abbe Mowshowitz, Yongtang Shi

Publications and Research

In this exploratory paper, we discuss quantitative graph-theoretical measures of network aesthetics. Related work in this area has typically focused on geometrical features (e.g., line crossings or edge bendiness) of drawings or visual representations of graphs which purportedly affect an observer’s perception. Here we take a very different approach, abandoning reliance on geometrical properties, and apply information-theoretic measures to abstract graphs and networks directly (rather than to their visual representaions) as a means of capturing classical appreciation of structural symmetry. Examples are used solely to motivate the approach to measurement, and to elucidate our symmetry-based mathematical theory of network aesthetics.

Comparing Tensorflow Deep Learning Performance Using Cpus, Gpus, Local Pcs And Cloud, John Lawrence, Jonas Malmsten, Andrey Rybka, Daniel A. Sabol, Ken Triplin

Publications and Research

Deep learning is a very computational intensive task. Traditionally GPUs have been used to speed-up computations by several orders of magnitude. TensorFlow is a deep learning framework designed to improve performance further by running on multiple nodes in a distributed system. While TensorFlow has only been available for a little over a year, it has quickly become the most popular open source machine learning project on GitHub. The open source version of TensorFlow was originally only capable of running on a single node while Google’s proprietary version only was capable of leveraging distributed systems. This has now changed. In this …

Monitoring The Dark Web And Securing Onion Services, John Schriner

Publications and Research

This paper focuses on how researchers monitor the Dark Web. After defining what onion services and Tor are, we discuss tools for monitoring and securing onion services. As Tor Project itself is research-driven, we find that the development and use of these tools help us to project where use of the Dark Web is headed.

Cst1101–Problem Solving With Computer Programming, Syllabus, Elena Filatova

Open Educational Resources

No abstract provided.

The Proscriptive Principle And Logics Of Analytic Implication, Thomas M. Ferguson

Dissertations, Theses, and Capstone Projects

The analogy between inference and mereological containment goes at least back to Aristotle, whose discussion in the Prior Analytics motivates the validity of the syllogism by way of talk of parts and wholes. On this picture, the application of syllogistic is merely the analysis of concepts, a term that presupposes—through the root ἀνά + λύω —a mereological background.

In the 1930s, such considerations led William T. Parry to attempt to codify this notion of logical containment in his system of analytic implication AI. Parry’s original system AI was later expanded to the system PAI. The hallmark of Parry’s systems—and of …