Computer Sciences Commons^™

Understanding Water Consumption And Energy Trends In New York City, Wen Yong Huang, Johann Thiel

Publications and Research

In this study, we will be using the NYC Open Data website to examine publicly available data sets on water and energy consumption in New York City. In particular, we will use various scientific programming and machine learning modules in Python to analyze and visualize trends in water and energy usage within the five boroughs.

The Most Powerful Thing, Caitlin Jankiewicz

Lake Union Herald

No abstract provided.

Image Processing Algorithms For Elastin Lamellae Inside Cardiovascular Arteries, Mahmoud Habibnezhad

School of Computing: Dissertations, Theses, and Student Research

Automated image processing methods are greatly needed to replace the tedious, manual histology analysis still performed by many physicians. This thesis focuses on pathological studies that express the essential role of elastin lamella in the resilience and elastic properties of the arterial blood vessels. Due to the stochastic nature of the shape and distribution of the elastin layers, their morphological features appear as the best candidates to develop a mathematical formulation for the resistance behavior of elastic tissues. However, even for trained physicians and their assistants, the current measurement procedures are highly error-prone and prolonged. This thesis successfully integrates such …

Performance Evaluation Of 3rd Normal Form Decompositions, Ben Mathew

Theses and Dissertations

When a relational database is chosen, normalization theory is a set of guidelines that may lead to efficient database designs. Thus, normalization of tables in a database is a common process used for the analysis of relational databases. Sufficient normalization of databases aims to decompose existing relational tables in order to minimize database redundancy while preserving dependencies between attributes. It also facilitates correct insertion, deletion, and modification of data in the database. Given an un-normalized relational database, a redesign with no data redundancy and which is guaranteed to preserve dependencies is not always achievable. Previous studies have shown that it …

Data Mining And Predictive Policing, Chanté L. Stewart-Wallace

Theses, Dissertations and Culminating Projects

This paper focuses on the operation and utilization of predictive policing software that generates spatial and temporal hotspots. There is a literature review that evaluates previous work surrounding the topics branched from predictive policing. It dissects two different crime datasets for San Francisco, California and Chicago, Illinois. Provided, is an in depth comparison between the datasets using both statistical analysis and graphing tools. Then, it shows the application of the Apriori algorithm to re-enforce the formation of possible hotspots pointed out in a actual predictive policing software. To further the analysis, targeted demographics of the study were evaluated to create …

A Privacy-Preserving Framework For Collaborative Association Rule Mining In Cloud, Salha Albehairi

Theses, Dissertations and Culminating Projects

Collaborative Data Mining facilitates multiple organizations to integrate their datasets and extract useful knowledge from their joint datasets for mutual benefits. The knowledge extracted in this manner is found to be superior to the knowledge extracted locally from a single organization’s dataset. With the rapid development of outsourcing, there is a growing interest for organizations to outsource their data mining tasks to a cloud environment to effectively address their economic and performance demands. However, due to privacy concerns and stringent compliance regulations, organizations do not want to share their private datasets neither with the cloud nor with other participating organizations. …

Commonsense Knowledge In Sentiment Analysis Of Ordinance Reactions For Smart Governance, Manish Puri

Theses, Dissertations and Culminating Projects

Smart Governance is an emerging research area which has attracted scientific as well as policy interests, and aims to improve collaboration between government and citizens, as well as other stakeholders. Our project aims to enable lawmakers to incorporate data driven decision making in enacting ordinances. Our first objective is to create a mechanism for mapping ordinances (local laws) and tweets to Smart City Characteristics (SCC). The use of SCC has allowed us to create a mapping between a huge number of ordinances and tweets, and the use of Commonsense Knowledge (CSK) has allowed us to utilize human judgment in mapping. …

A Privacy-Aware Framework For Friend Recommendations In Online Social Networks, Mona Fahad Alkanhal

Theses, Dissertations and Culminating Projects

Online social networks (OSN), such as Facebook, Twitter, and LinkedIn, have revolutionized the way how people share information and stay connected with family and friends. Along this direction, user’s privacy has been a significant concern to all users in the social networks. In this thesis, we propose a privacyaware framework that allows users to outsource their encrypted profile data to a cloud environment. In order to achieve better security and efficiency, our framework utilizes a hybrid approach that consists of Paillier’s encryption scheme and AES. Furthermore, we develop a privacy-aware friend recommendation protocol that recommends new friends to social network …

A Survey On The Role Of Individual Differences On Visual Analytics Interactions: Masters Project Report, Jesse Huang, Alvitta Ottley

All Computer Science and Engineering Research

There is ample evidence in the visualization commu- nity that individual differences matter. These prior works high- light various traits and cognitive abilities that can modulate the use of the visualization systems and demonstrate a measurable influence on speed, accuracy, process, and attention. Perhaps the most important implication of this body of work is that we can use individual differences as a mechanism for estimating people’s potential to effectively leverage visual interfaces or to identify those people who may struggle. As visual literacy and data fluency continue to become essential skills for our everyday lives, we must embrace the growing …

Smart Home Audio Assistant, Xipeng Wang

All Computer Science and Engineering Research

This report introduces an audio processing algorithm. It provides a way to access smart devices using audio. Although there are many audio assistants already on the market, most of them will not be able to control the smart devices. Therefore, this new system presented in this report will provide a way to analysis the customer’s questions. Then the algorithm will be able to query smart device information, modify the schedule or provide the reason for some arrangement.

Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre

Honors Scholar Theses

Abnormal ocular motility is a common manifestation of many underlying pathologies particularly those that are neurological. Dynamics of saccades, when the eye rapidly changes its point of fixation, have been characterized for many neurological disorders including concussions, traumatic brain injuries (TBI), and Parkinson’s disease. However, widespread saccade analysis for diagnostic and research purposes requires the recognition of certain eye movement parameters. Key information such as velocity and duration must be determined from data based on a wide set of patients’ characteristics that may range in eye shapes and iris, hair and skin pigmentation [36]. Previous work on saccade analysis has …

Powers And Behaviors Of Directed Self-Assembly, Trent Allen Rogers

Graduate Theses and Dissertations

In nature there are a variety of self-assembling systems occurring at varying scales which give rise to incredibly complex behaviors. Theoretical models of self-assembly allow us to gain insight into the fundamental nature of self-assembly independent of the specific physical implementation. In Winfree's abstract tile assembly model (aTAM), the atomic components are unit square "tiles" which have "glues" on their four sides. Beginning from a seed assembly, these tiles attach one at a time during the assembly process in an asynchronous and nondeterministic manner.

We can gain valuable insights into the nature of self-assembly by comparing different models of self-assembly …

Assume-Guarantee Reasoning Using A Cyber Security Ontology, Ali Abdurhman Alfageeh

Theses and Dissertations

Design of a network is a challenging problem as it involves the integration of several complex components such as routers, servers, computers, smart devices. This is further complicated by the need to have robust security policies implemented to prevent violation of confidentiality as the networked devices interact. The design of such complex networked systems demand a more rigorous approach to the modeling and analysis, which can be inherited from the field of Software engineering. Presently, network or security engineers do not use a system/software engineering approach to design and build cybersecurity systems. Thus, we propose a system/software engineering approach to …

Encryption Algorithms For Data Security In Local Area Network, Asmaa Essam Alhibshi

Theses and Dissertations

Cryptography plays an important part in data and information security. An overview of cryptography is given in the paper. This paper tries to compare most commonly used encryption algorithms RSA and AES, with their performance analysis on java and C++. At first a brief introduction on types of cryptography i.e. symmetric and asymmetric encryption algorithm. Then previous work on these encryption algorithms is discussed and their performance comparison in the form of table is given. Then the objectives of this thesis is given. In chapter 3, a detailed description of ciphering algorithms, RSA, AES, TCP and UDP is provided. Chapter …

A Bystander's Dilemma: Participatory Design Study Of Privacy Expectations For Smart Home Devices, Oriana Mcdonough

Renée Crown University Honors Thesis Projects - All

Traditional homes have become increasingly filled with Internet-connected devices, turning them into “smart homes.” Currently, research around privacy concerns with smart home devices has focused on the end users. The goal for our research is to understand the perceptions and desired privacy mechanisms from the perspective of a different stakeholder, i.e., the bystanders. Bystanders in this context are individuals who are not the owner or primary user of smart home devices but are potentially affected by the device usage, such as house guests or family members. In order to understand this, we conducted a focus group study with co-design activities …

The Golden Ticket: How Blockchain Technology Can Be Implemented Into Event Ticketing, Jack Singer

Renée Crown University Honors Thesis Projects - All

When the group/individual named Satoshi Nakamoto first conceptualized blockchain in 2008, it served as the underlying foundation to the cryptocurrency Bitcoin. In the years following, cryptocurrencies alike experiences massive gains in profitability; however, after the bubble had burst organizations began to look at the technology from a more academic standpoint. It was quickly found out that there is a massive application for blockchain in almost all sectors of industry from bulk stores (Walmart) to banking (IBM). This paper will explore how blockchain technology can be implemented into event ticketing, more specifically concerts. The current landscape of the industry is under …

Exploring Data Science: Understanding, Predicting, & Visualizing Crime In Syracuse, Ryan French

Renée Crown University Honors Thesis Projects - All

With the advent of the open data portal for the city of Syracuse came an opportunity previously impossible; anyone could download, mine, and visualize information about Syracuse direct from the source. Over the course of this project, I will be performing these processes on a selection of crime data from 2017 in order to better understand the patterns of crime in Syracuse, where they occur, and if it can be predicted whether or not a crime will lead to an arrest.

This project will begin with an overview of the data, how it was obtained, and the meanings of the …

Watersheds For Semi-Supervised Classification, Aditya Challa, Sravan Danda, B. S.Daya Sagar, Laurent Najman

Journal Articles

Watershed technique from mathematical morphology (MM) is one of the most widely used operators for image segmentation. Recently watersheds are adapted to edge weighted graphs, allowing for wider applicability. However, a few questions remain to be answered - How do the boundaries of the watershed operator behave? Which loss function does the watershed operator optimize? How does watershed operator relate with existing ideas from machine learning. In this letter, a framework is developed, which allows one to answer these questions. This is achieved by generalizing the maximum margin principle to maximum margin partition and proposing a generic solution, morphMedian, resulting …

A Deep Learning Approach To Diagnosing Schizophrenia, Justin Barry

Electronic Theses and Dissertations

In this article, the investigators present a new method using a deep learning approach to diagnose schizophrenia. In the experiment presented, the investigators have used a secondary dataset provided by National Institutes of Health. The aforementioned experimentation involves analyzing this dataset for existence of schizophrenia using traditional machine learning approaches such as logistic regression, support vector machine, and random forest. This is followed by application of deep learning techniques using three hidden layers in the model. The results obtained indicate that deep learning provides state-of-the-art accuracy in diagnosing schizophrenia. Based on these observations, there is a possibility that deep learning …

Realtime Editing In Virtual Reality For Room Scale Scans, Charles Greenwood

Electronic Theses and Dissertations

This work presents a system for the design and implementation of tools that support the editing of room-scale scans within a virtual reality environment, in real time. The moniker REVRRSS ("reverse") thus stands for Real-time Editing (in) Virtual Reality (of) Room Scale Scans. The tools were evaluated for usefulness based upon whether they meet the criterion of real time usability. Users evaluated the editing experience with traditional keyboard-video-mouse compared to a head mounted display and hand-held controllers for Virtual Reality. Results show that users prefer the VR approach. The quality of the finished product when using VR is comparable to …

Synergistic Visualization And Quantitative Analysis Of Volumetric Medical Images, Neslisah Torosdagli

Electronic Theses and Dissertations

The medical diagnosis process starts with an interview with the patient, and continues with the physical exam. In practice, the medical professional may require additional screenings to precisely diagnose. Medical imaging is one of the most frequently used non-invasive screening methods to acquire insight of human body. Medical imaging is not only essential for accurate diagnosis, but also it can enable early prevention. Medical data visualization refers to projecting the medical data into a human understandable format at mediums such as 2D or head-mounted displays without causing any interpretation which may lead to clinical intervention. In contrast to the medical …

Machine Learning From Casual Conversation, Awrad Mohammed Ali

Electronic Theses and Dissertations

Human social learning is an effective process that has inspired many existing machine learning techniques, such as learning from observation and learning by demonstration. In this dissertation, we introduce another form of social learning, Learning from a Casual Conversation (LCC). LCC is an open-ended machine learning system in which an artificially intelligent agent learns from an extended dialog with a human. Our system enables the agent to incorporate changes into its knowledge base, based on the human's conversational text input. This system emulates how humans learn from each other through a dialog. LCC closes the gap in the current research …

Federal, State And Local Law Enforcement Agency Interoperability Capabilities And Cyber Vulnerabilities, Tyrone Trapnell

Electronic Theses and Dissertations

The National Data Exchange (N-DEx) System is the central informational hub located at the Federal Bureau of Investigation (FBI). Its purpose is to provide network subscriptions to all Federal, state and local level law enforcement agencies while increasing information collaboration across all domains. The National Data Exchange users must satisfy the Advanced Permission Requirements, confirming the terms of N-DEx information use, and the Verification Requirement (verifying the completeness, timeliness, accuracy, and relevancy of N-DEx information) through coordination with the record-owning agency (Management, 2018). A network infection model is proposed to simulate the spread impact of various cyber-attacks within Federal, state …

Efficient String Graph Construction Algorithm, S.M. Iqbal Morshed

Electronic Theses and Dissertations

In the field of genome assembly research where assemblers are dominated by de Bruijn graph-based approaches, string graph-based assembly approach is getting more attention because of its ability to losslessly retain information from sequence data. Despite the advantages provided by a string graph in repeat detection and in maintaining read coherence, the high computational cost for constructing a string graph hinders its usability for genome assembly. Even though different algorithms have been proposed over the last decade for string graph construction, efficiency is still a challenge due to the demand for processing a large amount of sequence data generated by …

Predicting Students' Academic Performance With Decision Tree And Neural Network, Junshuai Feng

Electronic Theses and Dissertations

Educational Data Mining (EDM) is a developing research field that involves many techniques to explore data relating to educational background. EDM can analyze and resolve educational data with computational methods to address educational questions. Similar to EDM, neural networks have been utilized in widespread and successful data mining applications. In this paper, synthetic datasets are employed since this paper aims to explore the methodologies such as decision tree classifiers and neural networks to predict student performance in the context of EDM. Firstly, it introduces EDM and some relative works that have been accomplished previously in this field along with their …

Describing Images By Semantic Modeling Using Attributes And Tags, Mahdi Mahmoudkalayeh

Electronic Theses and Dissertations

This dissertation addresses the problem of describing images using visual attributes and textual tags, a fundamental task that narrows down the semantic gap between the visual reasoning of humans and machines. Automatic image annotation assigns relevant textual tags to the images. In this dissertation, we propose a query-specific formulation based on Weighted Multi-view Non-negative Matrix Factorization to perform automatic image annotation. Our proposed technique seamlessly adapt to the changes in training data, naturally solves the problem of feature fusion and handles the challenge of the rare tags. Unlike tags, attributes are category-agnostic, hence their combination models an exponential number of …

Quality Diversity: Harnessing Evolution To Generate A Diversity Of High-Performing Solutions, Justin Pugh

Electronic Theses and Dissertations

Evolution in nature has designed countless solutions to innumerable interconnected problems, giving birth to the impressive array of complex modern life observed today. Inspired by this success, the practice of evolutionary computation (EC) abstracts evolution artificially as a search operator to find solutions to problems of interest primarily through the adaptive mechanism of survival of the fittest, where stronger candidates are pursued at the expense of weaker ones until a solution of satisfying quality emerges. At the same time, research in open-ended evolution (OEE) draws different lessons from nature, seeking to identify and recreate processes that lead to the type …

Analysis Literatures Of Machine Learning And Neural Networks For Real Time Scheduling, Phong Nguyenho, Mark Nguyen

Recent Advances in Real-Time Systems

Real time scheduling problems are present in every aspect of software development. An optimized real time scheduling scheme would determine the performance of an operating system. There are many different approaches that real time scheduling researchers developed to tackle scheduling problems in many computer systems that have great important roles in keeping our modern society running smoothly. Neural-network real time scheduling is one of those approaches that can solve many computer scheduling problems. As computing technology advanced, more and more real time scheduling problems arise that need new solutions to keep up with the demand of faster computer systems. In …

Processing Narratives By Means Of Action Languages, Craig Olson

Computer Science Theses, Dissertations, and Student Creative Activity

In this work we design a narrative understanding system Text2ALM that can be used in Question Answering domains. System Text2ALM utilizes an action language 𝒜ℒℳ to perform inferences on complex interactions of events described in narratives. The methodology that Text2ALM follows in its implementation was originally outlined by Yuliya Lierler, Daniela Inclezan, and Michael Gelfond in 2017 via a manual process, and this work serves as a proof of concept in a large-scale environment. Our system automates the conversion of a narrative to an 𝒜ℒℳ model containing facts about the narrative. We make use of the VerbNet lexicon that we …

Grant Anon Minigames Extension, Justin Robbins

Theses/Capstones/Creative Projects

The Grant Anon system was designed to be a casualized version of the real-time strategy genre, a genre usually known for its difficulty and competitiveness because of Starcraft II, the most popular game in the genre. Grant Anon was designed as part of a capstone project, and this report details the extension that was created to add an additional element designed to make it easier for any player to enjoy Grant Anon: minigames. These minigames serve to reduce the skill needed to participate effectively in Grant Anon. This is accomplished by providing an alternative means of gaining an advantage over …