Computer Sciences Commons^™

Infrared And Visible Image Fusion Based On Oversampled Graph Filter Banks, Chunyan Song, Xueying Gao, Yu-Long Qiao, Kaige Zhang

Computer Science Student Research

The infrared image (RI) and visible image (VI) fusion method merges complementary information from the infrared and visible imaging sensors to provide an effective way for understanding the scene. The graph filter bank-based graph wavelet transform possesses the advantages of the classic wavelet filter bank and graph representation of a signal. Therefore, we propose an RI and VI fusion method based on oversampled graph filter banks. Specifically, we consider the source images as signals on the regular graph and decompose them into the multiscale representations with M-channel oversampled graph filter banks. Then, the fusion rule for the low-frequency subband is …

Securing The Emerging Technologies Of Autonomous And Connected Vehicles, Shahab Tayeb, Matin Pirouz

Mineta Transportation Institute

The Internet of Vehicles (IoV) aims to establish a network of autonomous and connected vehicles that communicate with one another through facilitation led by road-side units (RSUs) and a central trust authority (TA). Messages must be efficiently and securely disseminated to conserve resources and preserve network security. Currently, research in this area lacks consensus about security schemes and methods of disseminating messages. Furthermore, a current deficiency of information regarding resource optimization prevents further efficient development of this network. This paper takes an interdisciplinary approach to these issues by merging both cybersecurity and data science to optimize and secure the network. …

Cis 356 - Fundamentals Of Cybersecurity And Intelligence Gathering, Fahad Chowdhury, Nyc Tech-In-Residence Corps

Open Educational Resources

Syllabus for the course: CIS 356: "Fundamentals of Cybersecurity and Intelligence Gathering" delivered at Lehman College in Spring 2020 by Fahad Chowdhury as part of the Tech-in-Residence Corps program.

Cis 356: Fundamentals Of Cybersecurity And Intelligence Gathering - Case Study Assignment, Fahad Chowdhury, Nyc Tech-In-Residence Corps

Open Educational Resources

Assignment for the course: CIS 356: Fundamentals of Cybersecurity and Intelligence Gathering - "Case Study Assignment" delivered at Lehman College in Spring 2020 by Fahad Chowdhury as part of the Tech-in-Residence Corps program.

Cis 356: Fundamentals Of Cybersecurity And Intelligence Gathering - Confidentiality, Integrity, Availability, Fahad Chowdhury, Nyc Tech-In-Residence Corps

Open Educational Resources

Lecture for the course: CIS 356: Fundamentals of Cybersecurity and Intelligence Gathering - "Confidentiality, Integrity, Availability" (Week One) delivered at Lehman College in Spring 2020 by Fahad Chowdhury as part of the Tech-in-Residence Corps program.

Cis 356: Fundamentals Of Cybersecurity And Intelligence Gathering - Vulnerabilities And Exploits, Fahad Chowdhury, Nyc Tech-In-Residence Corps

Open Educational Resources

Lecture for the course: CIS 356: Fundamentals of Cybersecurity and Intelligence Gathering - "Vulnerabilities and Exploits" (Week Two) delivered at Lehman College in Spring 2020 by Fahad Chowdhury as part of the Tech-in-Residence Corps program.

Cis 356: Fundamentals Of Cybersecurity And Intelligence Gathering - Encryption And Hashing, Fahad Chowdhury, Nyc Tech-In-Residence Corps

Open Educational Resources

Lecture for the course: CIS 356: Fundamentals of Cybersecurity and Intelligence Gathering - "Encryption and Hashing" (Week Four) delivered at Lehman College in Spring 2020 by Fahad Chowdhury as part of the NYC Tech-in-Residence Corps program.

Cis 356-Zi81: Intermediate-Level Topics In Computer Applications (Spring 2020), Fahad Choudhury, Nyc Tech-In-Residence Corps

Open Educational Resources

Syllabus for CIS 356-ZI81: Intermediate-Level Topics in Computer Applications (Spring 2020)

Csci 380 - Digital Operations And Cybersecurity Management (Syllabus), Eric Spector, Nyc Tech-In-Residence Corps

Open Educational Resources

Syllabus for the course "CSCI 380 - Digital Operations and Cybersecurity Management" delivered at the John Jay COllege in Spring 2020 by Eric Spector as part of the Tech-in-Residence Corps program.

Computer Simulations Of Muscle Driven Undulatory Locomotion, Ye Luo

Dissertations

A novel muscle driven method is developed to mimic contracting and expanding of muscles, in a fish-like swimming body, which cause its body flapping in the transversal direction and create thrust force to push its body to cruise in the longitudinal direction. The muscle deformation is realized by using the RATTLE constraint algorithm. The turbulent fluids are treated by a multi-relaxation time lattice Boltzmann method with a large eddy simulation. The fish body is dealt with a lattice spring model and interactions between fluids and solid structures are handled by a direct-forcing immersed boundary method. Validations are conducted by comparing …

Explainable Deep Learning For Medical Image Analysis, Brennan Rhoadarmer

UCARE: Research Products

Explainable Deep Learning for Medical Image Analysis is a project focused on improving the ability for deep learning models to explain the reasoning behind their classification in order to improve their viability in the medical field, where explanations of decisions is critical for the care of patients. In order to explore this topic, we work to implement GradCAM, which is a new method of determining the cause classification in models by tracing back through the model layers to the input.

A New Intra-Cluster Scheduling Scheme For Real-Time Flows In Wireless Sensor Networks, Gohar Ali, Fernando Moreira, Omar Alfandi, Babar Shah, Mohammed Ilyas

All Works

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Real-time flows using time division multiple access (TDMA) scheduling in cluster-based wireless sensor networks try to schedule more flows per time frame to minimize the schedule length to meet the deadline. The problem with the previously used cluster-based scheduling algorithm is that intra-cluster scheduling does not consider that the clusters may have internal or outgoing flows. Thus, intra-cluster scheduling algorithms do not utilize their empty time-slots and thus increase schedule length. In this paper, we propose a new intra-cluster scheduling algorithm by considering that clusters may have having internal or outgoing …

A Feel For The Game: Ai, Computer Games And Perceiving Perception, Marc A. Ouellette, Steven Conway

English Faculty Publications

I walk into the room and the smell of burning wood hits me immediately. The warmth from the fireplace grows as I step nearer to it. The fire needs to heat the little cottage through the night so I add a log to the fire. There are a few sparks and embers. I throw a bigger log onto the fire and it drops with a thud. Again, there are barely any sparks or embers. The heat and the smell stay the same. They don’t change and I do not become habituated to it. Rather, they are just a steady stream, …

Computer Science Without Computers: A Guide To Teaching Concepts Of Computer Science Without Access To Computers Or Other Technological Devices, Anna Nagy 20

Honor Scholar Theses

No abstract provided.

A Parallel Algorithm And Implementation To Compute Spatial Autocorrelation (Hotspot) Using Matlab, Mingjun Li

Master's Theses (2009 -)

Being a spatial autocorrelation visualization tool in recent years, hotspot is often used in various fields, such as disease analysis, crime analysis, and weather conditions analysis and prediction in a certain area. Most of the research in hot spot analysis is in applying the concept to a variety of fields and to gain insights on the statistical significance prevalent in the clustering of data. Only a few of them discussed the efficiency and optimization of the algorithm. Commonly, these kinds of analyses would be based upon a huge dataset about space and time, and the conventional algorithm would take too …

A Critical Study Of Geospatial Algorithm Use In Crime Analysis And Predictive Policing, Katy Weathington

Master's Theses (2009 -)

We examine in detail two geospatial analysis algorithms commonly used in predictive policing. The k-means clustering algorithm is used to partition input data into k clusters, while Kernel Density Estimation algorithms convert geospatial data into a 2-dimensional probability distribution function. Both algorithms serve unique roles in predictive policing, helping to inform the allocation of limited police resources. Through critical analysis of the k-means algorithm, we found that parameter choice can greatly impact how crime in a city is clustered, which therefor impacts how mental models of crime in the city are developed. Interviews with crime analysts who regularly used k-means …

An Educational Operating System Supporting Computer Security, Patrick Joseph Mcgee

Master's Theses (2009 -)

It is uncommon to teach computer security concepts using an embedded operating system. Few educational operating systems are implemented in systems courses, and a small subset of them are used to teach hardware-related security elements such as system calls. This work explores relevant approaches to teaching low-level security concepts, including difficulties associated with building a hands-on learning environment. This work also presents additions to the Embedded Xinu kernel that support system calls and memory protection on a Raspberry Pi 3 B+. Provided sample assignments are intended to help give students a solid understanding of intricate hardware details. Results from an …

Machine Learning And Data Mining-Based Methods To Estimate Parity Status And Age Of Wild Mosquito Vectors Of Infectious Diseases From Near-Infrared Spectra, Masabho Peter Milali

Dissertations (1934 -)

Previous studies show that a trained partial least square regresser [sic] (PLSR) from near-infrared spectra classify laboratory and semi-field raised mosquitoes into less than or ≥ to seven days old with an average accuracy of 80%. This dissertation demonstrates that training models on near-infrared spectra (NIRS) using artificial neural network (ANN) as an architecture yields models with higher accuracies than training models using partial least squares (PLS) as an architecture. In addition, irrespective of the model architecture used, direct training of a binary classifier scores higher accuracy than training a regresser and interpreting it as a binary classifier. Furthermore, for …

Dependable And Scalable Public Ledger For Policy Compliance, A Blockchain Based Approach, Zhou Wu

Dissertations (1934 -)

Policies and regulations, such as the European Union General Data Protection Regulation (EU GDPR), have been enforced to protect personal data from abuse during storage and processing. We design and implement a prototype scheme that could 1) provide a public ledger of policy compliance to help the public make informative decisions when choosing data services; 2) provide support to the organizations for identifying violations and improve their ability of compliance. Honest organizations could then benefit from their positive records on the public ledger. To address the scalability problem inherent in the Blockchain-based systems, we develop algorithms and leverage state channels …

Gradual Program Analysis, Samuel Estep

Senior Honors Theses

Dataflow analysis and gradual typing are both well-studied methods to gain information about computer programs in a finite amount of time. The gradual program analysis project seeks to combine those two techniques in order to gain the benefits of both. This thesis explores the background information necessary to understand gradual program analysis, and then briefly discusses the research itself, with reference to publication of work done so far. The background topics include essential aspects of programming language theory, such as syntax, semantics, and static typing; dataflow analysis concepts, such as abstract interpretation, semilattices, and fixpoint computations; and gradual typing theory, …

Text Analytics, Nlp, And Accounting Research, Richard M. Crowley

Research Collection School Of Accountancy

The presentation covered: What is text analytics and NLP?; How text analytics has evolved in the accounting literature since the 1980s; What current (as of 2020) methods are used in the literature; What methods are on the horizon.

From Cellular To Holistic: Development Of Algorithms To Study Human Health And Diseases, Casey Anne Cole

Theses and Dissertations

The development of theoretical computational methods and their application has become widespread in the world today. In this dissertation, I present my work in the creation of models to detect and describe complex biological and health related problems. The first major part of my work centers around the creation and enhancement of methods to calculate protein structure and dynamics. To this end, substantial enhancement has been made to the software package REDCRAFT to better facilitate its usage in protein structure calculation. The enhancements have led to an overall increase in its ability to characterize proteins under difficult conditions such as …

A Cue Adaptive Decoder For Controllable Neural Response Generation, Weichao Wang, Shi Feng, Wei Gao, Daling Wang, Yifei Zhang

Research Collection School Of Computing and Information Systems

In open-domain dialogue systems, dialogue cues such as emotion, persona, and emoji can be incorporated into conversation models for strengthening the semantic relevance of generated responses. Existing neural response generation models either incorporate dialogue cue into decoder’s initial state or embed the cue indiscriminately into the state of every generated word, which may cause the gradients of the embedded cue to vanish or disturb the semantic relevance of generated words during back propagation. In this paper, we propose a Cue Adaptive Decoder (CueAD) that aims to dynamically determine the involvement of a cue at each generation step in the decoding. …

Understanding The Relation Between Repeat Developer Interactions And Bug Resolution Times In Large Open Source Ecosystems: A Multisystem Study, Subhajit Datta, Reshma Roychoudhuri, Subhashis Majumder

Research Collection School Of Computing and Information Systems

Large‐scale software systems are being increasingly built by distributed teams of developers who interact across geographies and time zones. Ensuring smooth knowledge transfer and the percolation of skills within and across such teams remain key challenges for organizations. Towards addressing this challenge, organizations often grapple with questions around whether and how repeat collaborations between members of a team relate to outcomes of important activities. In the context of this paper, the word ‘repeat interaction’ does not imply a greater number of interactions; it refers to repeat interaction between a pair of developers who have collaborated before. In this paper, we …

A Semi-Automatic Integrated Framework For Non-English Sentiment Lexicons, Abdullah Kaity Mohammed Salem

Student Works (2020-2029)

There has been significant growth in social media networks in the last few years. Posting opinions and messages on social networking websites has become a popular activity on the Internet. The data sources are necessary for business intelligence and market analytics, as human opinions form a major indicator of human desires and behaviour. This has resulted in the development of a new study field called sentiment analysis. This includes the analysis, evaluation and interpretation of the opinions with the help of text mining and Natural Language Processing (NLP) processes, for identifying the text polarity, as positive, neutral or negative. It …

Multi-Tier Classification Based On Sentiment, Type, Emotion And Purpose For Online Diabetes Community, Ratan Singh Wandeep Kaur

Student Works (2020-2029)

The evolution of social media platforms has created a niche for users to increasingly turn to such sites in order to share and exchange health related information. Facebook being one of the largest social networking sites has only encouraged such exchange thus mounting to a sheer amount of data that is hidden within unstructured text. The aim of this research is to propose a multi-tier classification based on sentiment, type, emotion and purpose (STEP) to classify data collected from diabetes community within Facebook. There are three tiers within the proposed STEP framework namely type, purpose and sentiment (and emotion within …

Raising Funds In The Era Of Digital Economy, Deserina Sulaeman

Dissertations and Theses Collection (Open Access)

The rapid advancement in technology and internet penetration have substantially increased the number of economic transactions conducted online. Platforms that connect economic agents play an important role in this digital economy. The unbridled proliferation of digital platforms calls for a closer examination of the factors that could affect the welfare of the increasing number of economic agents who participate in them.

This dissertation examines the factors that could affect the welfare of agents using the setting of a crowdfunding platform where fundraisers develop campaigns to solicit funding from potential donors. These factors can be broadly categorized into three distinct groups: …

Smart Cities At Play: Technology And Emerging Forms Of Playfulness, Konstantinos Papangelis, Michael Saker, Catherine Jones

Articles

Editorial. No abstract is available.

Preparing For The Future: The Effects Of Financial Literacy On Financial Planning For Young Professionals, Tanay Singh

Senior Theses

Purpose – Many people between the age of 20 and 34 have not considered planning financially for the future in any significant capacity and in doing so, they limit their potential savings. The purpose of this study is to examine what financial expectations are for people in the early stages of their career and determine if improving financial literacy and revealing financial realities helps to produce more accurate or realistic expectations. Ultimately, the goal is to better prepare participants in the study for the working world and increased responsibilities outside of the college/university environment by getting them to start thinking …

Lablineup: An Intuitive Web Application For Queueing Help Requests In Academic Labs, Graham Mcdonald

Senior Theses

LabLineup is a start-up project designed to address the needs of large, lab-based classes, where teaching assistants (TAs) struggle to assist students in the order in which they request help. LabLineup is a lightweight web application that allows TAs and professors to accept requests for help in order. LabLineup allows professors to view the requests for a lab and see frequently asked questions that can be addressed en masse rather than individually. LabLineup also allows students to provide TA feedback. LabLineup addresses issues arising from requesting help in large, lab-based classes in the most efficient manner possible.