Computer Sciences Commons^™

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 …

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 …

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 …

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 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 …

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, …

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 …

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. …

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 …

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 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 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.

Tandem 2.0: Image And Text Data Generation Application, Christopher J. Vitale

Dissertations, Theses, and Capstone Projects

First created as part of the Digital Humanities Praxis course in the spring of 2012 at the CUNY Graduate Center, Tandem explores the generation of datasets comprised of text and image data by leveraging Optical Character Recognition (OCR), Natural Language Processing (NLP) and Computer Vision (CV). This project builds upon that earlier work in a new programming framework. While other developers and digital humanities scholars have created similar tools specifically geared toward NLP (e.g. Voyant-Tools), as well as algorithms for image processing and feature extraction on the CV side, Tandem explores the process of developing a more robust and user-friendly …

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 …

A Novel Approach For Library Materials Acquisition Using Discrete Particle Swarm Optimization, Daniel A. Sabol

Publications and Research

The academic library materials acquisition problem is a challenge for librarian, since library cannot get enough funding from universities and the price of materials inflates greatly. In this paper, we analyze an integer mathematical model by considering the selection of acquired materials to maximize the average preference value as well as the budget execution rate under practical restrictions. The objective is to improve the Discrete Particle Swarm Optimization (DPSO) algorithm by adding a Simulate Annealing algorithm to reduce premature convergence. Furthermore, the algorithm is implemented in multiple threaded environment. The experimental results show the efficiency of this approach.

Automated Refactoring Of Legacy Java Software To Default Methods, Raffi 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 …

2d Vector Map And Database Design For Indoor Assisted Navigation, Luciano Caraciolo Albuquerque

Dissertations and Theses

In this paper we implemented a 2D Vector Map, map editor and Database design intended to provide an efficient way to convert cad files from indoor environments to a set of vectors representing hallways, doors, exits, elevators, and other entities embedded in a floor plan, and save them in a database for use by other applications, such as assisted navigation for blind people.

A graphical application as developed in C++ to allow the user to input a CAD DXF file, process the file to automatically obtain nodes and edges, and save the nodes and edges to a database for posterior …

Detecting Broken Pointcuts Using Structural Commonality And Degree Of Interest, Raffi Khatchadourian, Awais Rashid, Hidehiko Masuhara, Takuya Watanabe

Publications and Research

Pointcut fragility is a well-documented problem in Aspect-Oriented Programming; changes to the base-code can lead to join points incorrectly falling in or out of the scope of pointcuts. Deciding which pointcuts have broken due to base-code changes is a daunting venture, especially in large and complex systems. We present an automated approach that recommends pointcuts that are likely to require modification due to a particular base-code change, as well as ones that do not. Our hypothesis is that join points selected by a pointcut exhibit common structural characteristics. Patterns describing such commonality are used to recommend pointcuts that have potentially …

Rationality, Parapsychology, And Artificial Intelligence In Military And Intelligence Research By The United States Government In The Cold War, Guy M. Lomeo

Theses and Dissertations

A study analyzing the roles of rationality, parapsychology, and artificial intelligence in military and intelligence research by the United States Government in the Cold War. An examination of the methodology behind the decisions to pursue research in two fields that were initially considered irrational.

The History Of Algorithmic Complexity, Audrey A. Nasar

Publications and Research

This paper provides a historical account of the development of algorithmic complexity in a form that is suitable to instructors of mathematics at the high school or undergraduate level. The study of algorithmic complexity, despite being deeply rooted in mathematics, is usually restricted to the computer science curriculum. By providing a historical account of algorithmic complexity through a mathematical lens, this paper aims to equip mathematics educators with the necessary background and framework for incorporating the analysis of algorithmic complexity into mathematics courses as early on as algebra or pre-calculus.