Digital Commons Network^™

Problem Solving / Javascript Programming, Sarah Zelikovitz, Orit D. Gruber

Open Educational Resources

This Lab Experiment focuses on JavaScript Programming. Upon completing the lab, you will be able to understand the following:

· The definition of Algorithmic Problem Solving.

· The role of JavaScript in web pages.

· The concept of Iteration in computer programming.

Multi-Perspective Analysis For Derivative Financial Product Prediction With Stacked Recurrent Neural Networks, Natural Language Processing And Large Language Model, Ethan Lo

Dissertations, Theses, and Capstone Projects

This study developed a multi-perspective, AI-powered model for predicting E-Mini S&P 500 Index Futures prices, tackling the challenging market dynamics of these derivative financial instruments. Leveraging FinBERT for analysis of Wall Street Journal data alongside technical indicators, trader positioning, and economic factors, my stacked recurrent neural network built with LSTMs and GRUs achieves significantly improved accuracy compared to single sub-models. Furthermore, ChatGPT generation of human-readable analysis reports demonstrates the feasibility of using large language models in financial analysis. This research pioneers the use of stacked RNNs and LLMs for multi-perspective financial analysis, offering a novel blueprint for automated prediction and …

The Potential Of The Implementation Of Offline Robotic Programming Into Automation-Related Pedagogy, Max Rios Carballo, Xavier Brown

Publications and Research

In this study, the offline programming tool RoboDK is used to program industrial robots for the automation sector. The study explores the feasibility of using this non-disruptive robot programming software for classroom use; assesses how well RoboDK can be used to program various robots used in the industry; creates and tests various applications; and pinpoints technical obstacles that prevent a smooth link between offline programming and actual robots. Initial results indicate that RoboDK is an effective tool for deploying its offline programming code to a Universal Robot, UR3e. There are many potential for advanced applications. The goal of the project …

Stand-Up Comedy Visualized, Berna Yenidogan

Dissertations, Theses, and Capstone Projects

Stand-up comedy has become an increasingly popular form of comedy in the recent years and comedians reach audiences beyond the halls they are performing through streaming services, podcasts and social media. While comedic performances are typically judged by how 'funny' they are, which could be proxied by the frequency and intensity of laughs through the performance, comedians also explore untapped social issues and provoke conversation, especially in this age where interaction with artists goes beyond their act. It is easy to see commonalities in the topics addressed in comedians’ work such as relationships, race and politics.This project provides an interactive …

Classifying Sidewalk Materials Using Multi-Modal Data, Jiawei Liu

Dissertations and Theses

Navigating safely and independently presents considerable challenges for people who are blind or have low vision (BLV), as it requires a comprehensive understanding of their neighborhood environment. Our user study reveals that materials and objects on sidewalks play a crucial role in navigation tasks. Unfortunately, current methods for assessing sidewalk materials are suboptimal, often relying on labor-intensive and expensive manual assessments that fail to capture the full range of sidewalk features critical to individuals with BLV.

In response to this problem, this master’s thesis investigates deep learning approaches specifically designed for the classification of multi-modal sidewalk materials. The proposed framework …

Deception Detection Across Domains, Languages And Modalities, Subhadarshi Panda

Dissertations, Theses, and Capstone Projects

With the increase of deception and misinformation especially in social media, it has become crucial to develop machine learning methods to automatically identify deception. In this dissertation, we identify key challenges underlying text-based deception detection in a cross-domain setting, where we do not have training data in the target domain. We analyze the differences between domains and as a result develop methods to improve cross-domain deception detection. We additionally develop approaches that take advantage of cross-lingual properties to support deception detection across languages. This involves the usage of either multilingual NLP models or translation models. Finally, to better understand multi-modal …

Happiness And Policy Implications: A Sociological View, Sarah M. Kahl

Dissertations, Theses, and Capstone Projects

The World Happiness Report is released every year, ranking each country by who is “happier” and explaining the variables and data they have used. This project attempts to build from that base and create a machine learning algorithm that can predict if a country will be in a “happy” or “could be happier” category. Findings show that taking a broader scope of variables can better help predict happiness. Policy implications are discussed in using both big data and considering social indicators to make better and lasting policies.

A Machine Learning Approach To Predicting The Onset Of Type Ii Diabetes In A Sample Of Pima Indian Women, Meriem Benarbia

Dissertations, Theses, and Capstone Projects

Type II diabetes is a disease that affects how the body regulates and uses sugar (glucose) as a fuel. This chronic disease results in too much sugar circulating in the bloodstream. High blood sugar levels can lead to circulatory, nervous, and immune systems disorders. Machine learning (ML) techniques have proven their strength in diabetes diagnosis. In this paper, we aimed to contribute to the literature on the use of ML methods by examining the value of a number of supervised machine learning algorithms such as logistic regression, decision tree classifiers, random forest classifiers, and support vector classifiers to identify factors …

Needle In A Haystack: Detecting Subtle Malicious Edits To Additive Manufacturing G-Code Files, Caleb Beckwith, Harsh Sankar Naicker, Svara Mehta, Viba R. Udupa, Nghia Tri Nim, Varun Gadre, Hammond Pearce, Gary Mac

Publications and Research

Increasing usage of Digital Manufacturing (DM) in safety-critical domains is increasing attention on the cybersecurity of the manufacturing process, as malicious third parties might aim to introduce defects in digital designs. In general, the DM process involves creating a digital object (as CAD files) before using a slicer program to convert the models into printing instructions (e.g. g-code) suitable for the target printer. As the g-code is an intermediate machine format, malicious edits may be difficult to detect, especially when the golden (original) models are not available to the manufacturer. In this work we aim to quantify this hypothesis through …

Efficient Protocols For Multi-Party Computation, Tahereh Jafarikhah

Dissertations, Theses, and Capstone Projects

Secure Multi-Party Computation (MPC) allows a group of parties to compute a join function on their inputs without revealing any information beyond the result of the computation. We demonstrate secure function evaluation protocols for branching programs, where the communication complexity is linear in the size of the inputs, and polynomial in the security parameter. Our result is based on the circular security of the Paillier's encryption scheme. Our work followed the breakthrough results by Boyle et al. [9; 11]. They presented a Homomorphic Secret Sharing scheme which allows the non-interactive computation of Branching Programs over shares of the secret inputs. …

Artificial Intelligence And Game Theory Controlled Autonomous Uav Swarms, Janusz Kusyk, M. Umit Uyar, Kelvin Ma, Eltan Samoylov, Ricardo Valdez, Joseph Plishka, Sagor E. Hoque, Giorgio Bertoli, Jefrey Boksiner

Publications and Research

Autonomous unmanned aerial vehicles (UAVs) operating as a swarm can be deployed in austere environments, where cyber electromagnetic activities often require speedy and dynamic adjustments to swarm operations. Use of central controllers, UAV synchronization mechanisms or pre-planned set of actions to control a swarm in such deployments would hinder its ability to deliver expected services. We introduce artificial intelligence and game theory based flight control algorithms to be run by each autonomous UAV to determine its actions in near real-time, while relying only on local spatial, temporal and electromagnetic (EM) information. Each UAV using our flight control algorithms positions itself …

Two Techniques For Automated Logging Statement Evolution, Allan R. Spektor

Theses and Dissertations

This thesis presents and explores two techniques for automated logging statement evolution. The first technique reinvigorates logging statement levels to reduce information overload using degree of interest obtained via software repository mining. The second technique converts legacy method calls to deferred execution to achieve performance gains, eliminating unnecessary evaluation overhead.

Bracelet Reminder For Alzheimer’S, Jennifer Islam, Caroline Rodriguez, Farrukh Zia

Publications and Research

This project involves the design, construction and testing of a personal reminder device for elderly who suffer from Alzheimer’s using a clock system and LED wearable technology. The device consists of an RGB LED strip connected to a 7-segment display (which operates as a clock circuit) attached to a microcontroller board. The device uses visual output to alert the user at that certain time the color being emitted represents the reminder the user set for that time. The project involves two phases. In the first phase, an RGB LED strip will be used to make a wearable device and tested …

Quorum Blockchain Stress Evaluation In Different Environments, Daniel P. Mera

Student Theses

In today’s world, the Blockchain technology is used for different purposes has brought an increment in the development of different Blockchain platforms, services, and utilities for storing data securely and efficiently. Quorum Blockchain, an Ethereum fork created by JPMorgan Chase, has placed itself in one of the widely used, efficient and trustful Blockchain platforms available today. Because of the importance which Quorum is contributing to the world, it is important to test and measure different aspects of the platform, not only to prove how efficient the software can be but as well as to have a clear view on what …

A Purely Defeasible Argumentation Framework, Zimi Li

Dissertations, Theses, and Capstone Projects

Argumentation theory is concerned with the way that intelligent agents discuss whether some statement holds. It is a claim-based theory that is widely used in many areas, such as law, linguistics and computer science. In the past few years, formal argumentation frameworks have been heavily studied and applications have been proposed in fields such as natural language processing, the semantic web and multi-agent systems. Studying argumentation provides results which help in developing tools and applications in these areas. Argumentation is interesting as a logic-based approach to deal with inconsistent information. Arguments are constructed using a process like logical inference, with …

Integrating Multi-Source Weather Data For Deep Learning, Haidar A. Alanbari Mr

Dissertations and Theses

Big Data has been playing a major role in the domain of Deep Learning applications as many companies and institutions continue to find solutions and extract certain trends in fields of climate change, weather forecasting and meteorology. This project extracts weather events data from multiple data sources that are supported by National Centers for Environmental information (NCEI) [1] and Amazon Web Services (AWS) [2]. Data sources include Next-Generation NEXRAD [3] Doppler radar reflectivity, GOES-16 [4] multi-channel satellite imagery and NCEI [1] storm events. Then, it integrates and refines data in proper formats to be fed to the open-source Detectron [5] …

Shaping The Future Of Trusted Digital Identity: The Idef Registry With Health Information Use Cases, Noreen Y. Whysel

Publications and Research

No abstract provided.

A Hands-On Robotics Concentration Curricula In Engineering Technology Programs, Andy S. Zhang, Angran Xiao, Yu Wang, Farrukh Zia, Muhammad Ummy

Publications and Research

This paper discusses the creation of a robotic concentration with four courses to meet the industry demands for qualified graduates in product design and services. Advances in computer technology and electronics have created a new field called mechatronics. Nowadays almost all high tech products are mechatronics in nature. Products such as automotive subsystems (such as anti-lock braking systems and automatic steering systems), medical devices, environmental monitoring systems, service and surgical robots are all mechatronic products. The robotic concentration focus on one of the most popular and visible area of mechatronics: robotics. The creation of the four courses: Embedded Systems Fundamentals, …

Tolerance Sensitivity Analysis And Robust Optimal Design Method Of A Surface-Mounted Permanent Magnet Motor By Using A Hybrid Response Surface Method Considering Manufacturing Tolerances, Cha-Seung Jun, Byung-Il Kwon, Ohbong Kwon

Publications and Research

This paper presents a robust optimal design method using a hybrid response surface method (H-RSM) which directly finds an optimal point satisfying a target Z-value or a probability of failure. Through three steps, this paper achieves the goal that is to increase the open-circuit airgap flux (OCAF) in a surface-mounted permanent magnet motor and decrease its variation caused by variations of the airgap lengths including an additional one between permanent magnets and rotor back yoke. First, the OCAF equation is derived from the magnetic equivalent circuit (MEC) considering the additional airgap. Then, the equation is validated by comparing its results …

Solar And Rain Catching Canopy. Urban Oasis, Afolabi Ibitoye, Langston Clark, Elena Zimareva, Evan Banks, Alexander Aptekar

Publications and Research

The Urban Oasis is designed to work within existing “pocket parks” in New York City as a combined rainwater collector, personal electronics charging station and resting designation for New Yorkers. Intended to not only lessen the demand on the city power grid by using renewable energy to charge devices, the urban oasis is also intended to mitigate grey water overfill in New York’s combined sewer system and, in general, serve as a model for responsible environmental stewardship in urban areas.

The important technical aspects of the canopy specifically analyzed were:

a) how much rainwater could the canopy be expected to …

In Search Of Homo Sociologicus, Yunqi Xue

Dissertations, Theses, and Capstone Projects

The subject of this dissertation is to build an epistemic logic system that is able to show the spreading of knowledge and beliefs in a social network that contains multiple subgroups. Epistemic logic is the study of logical systems that express mathematical properties of knowledge and belief. In recent years, there have been increasing number of new epistemic logic systems that are focused on community properties such as knowledge and belief adoption among friends.

We are interested in revisable and actionable social knowledge/belief that leads to a large group action. Instead of centralized coordination, bottom-up approach is our focus. We …

Improving Disciplinary Literacy In An Electronics Course, Ohbong Kwon, Juanita C. But, Sunghoon Jang

Publications and Research

Electronics (EMT1255) is a required course for the Associate Degree in Applied Science (AAS) in Electromechanical Engineering Technology (EMT) at New York City College of Technology. EMT1255 introduces semiconductor devices and their applications in electronic-circuits. Students are expected to understand the structures and principles of semiconductor devices and the configuration and principles of basic electronic circuits. They also learn to analyze and design electronic circuits. In the lab setting, they acquire troubleshooting knowledge and hands-on technical skills. In this reading intensive course, students need to read the lab manual and a textbook of over 700 pages. Therefore, reading and understanding …

Cyber Security Risks In Public High Schools, Ion Goran

Student Theses

Today, just like other organizations, schools are vulnerable to cyber-attacks. This vulnerability has vividly revealed itself in recent years, with the number of attacks on public schools increasing and taking ever-changing forms. Today, the student’s grades, disciplinary notes, learning diagnoses, phone numbers, addresses, and another identifying information is all at risk of being exposed. Moreover, poor network security poses a dire threat to parents of school children whose personal records contain sensitive or dangerous information. The practical implications of these attacks require intervention or remedy to increase cyber security. Cyberattacks may take place when storage facilities or infected devices are …

Brief Study Of Classification Algorithms In Machine Learning, Ramesh Sankara Subbu

Dissertations and Theses

The purpose of this study is to briefly learn the theory and implementation of three most commonly used Machine Learning algorithms: k-Nearest Neighbors (kNN), Decision Trees and Naïve Bayes. All these algorithms fall under the Classification algorithm category of Unsupervised Machine Learning. This paper is constructed structurally in explaining the working theory behind each algorithm and an implementation of a Machine Learning problem solved by each algorithm. KNN algorithm is designed using Euclidean distance measurement and Decision Trees make use of ID3 algorithm as a basis. We conclude the study by providing an overall picture of its strengths and weaknesses …

Scale Up Bayesian Network Learning, Xiannian Fan

Dissertations, Theses, and Capstone Projects

Bayesian networks are widely used graphical models which represent uncertain relations between the random variables in a domain compactly and intuitively. The first step of applying Bayesian networks to real-word problems is typically building the network structure. Optimal structure learning via score-and-search has become an active research topic in recent years. In this context, a scoring function is used to measure the goodness of fit of a structure to given data, and the goal is to find the structure which optimizes the scoring function. The problem has been viewed as a shortest path problem, and has been shown to be …

Mobile Apps In Collection Development: Supporting A Mobile Learning Environment, Stefanie Havelka, Rebecca Arzola

Publications and Research

We will discuss our rationale and thoughts on why we believe mobile apps should be part of a library’s collection development policy. An updated policy with apps encourages a mobile learning environment that is technologically diverse while being holistically supportive of its users and research.

Mobile First Web And Content Strategy, Stefanie Havelka, David Stevens

Publications and Research

The paradigm shift from the traditional desktop to the mobile web experience is fast approaching, and providing relevant date, location and time-sensitive content to users via mobile devices becomes an essential piece of the overall web strategy. This presentation demonstrates the concepts, techniques and technologies used to develop both the overall mobile content strategy and user experience, as well as the aggregation and delivery of content to both the desktop and mobile form factors from a single content source.