Social and Behavioral Sciences Commons^™

Three Essays Applying Dynamic Models In Economics, Finance, And Machine Learning, Lucas C. Dowiak

Dissertations, Theses, and Capstone Projects

This dissertation is a composition in three parts. Collectively, these essays investigate dynamic methods and their application in the fields of Economics, Finance, and Machine Learning. It pulls liberally from all three. In particular, this dissertation makes repeated use of multi-state modeling frameworks popular in Economics to bring a faceted view to the underlying data and detect its hidden heterogeneity. The challenge of modeling financial assets and estimating their dependence is another focus. For stimulus, concepts in the Machine Learning field are brought in to aid or compete with established econometric techniques.

Econometric Applications of the Hierarchical Mixture-of-Experts

In this …

Me And Mathematics: “Doing What You’Re Talking About”: In Dialogue With My Family, Eden Morris

Dissertations, Theses, and Capstone Projects

This paper is a philosophically oriented accompaniment to my audio project (accessible through the following link: https://cuny.manifoldapp.org/projects/me-and-mathematics). Working together, the paper and audio collages form a call to action and a resource. My primary finding is the importance of doing what you’re talking about or exploring and implementing your ideas experientially. Doing what you’re talking about is important for effective teaching/learning and feeling in line with oneself. This working concept came to my attention during my research conversation with my oldest living relative, and then, again, with my youngest (non-baby) relative. This doing what you’re talking about is a way …

The Efficacy Of Using Machine Learning Techniques For Identifying And Classifying “Fake News”, Muhammad Islam

Dissertations, Theses, and Capstone Projects

In today's digital world, detecting fake news has emerged as a critical challenge, one that has significant effects on democracy and public discourse at large both regionally and globally. This research studies how diversity of news sources in training datasets affects how well machine learning models can classify fake vs true news. I used the Linear Support Vector Classification (LinearSVC) to create and compare two classification models: one was trained on a dataset that only had real news from a singular source, Reuters (Dataset 1), and the other was trained on a dataset that contained real news from Reuters, The …

Combining Cloud Architecting With Education, Sharon P. Pagidipati

Liberal Arts and Engineering Studies

I pursued the AWS Solutions Architect Professional Certification while applying my knowledge to build and revise technical solutions for an educational company known as EDFX.

Assessing Impact Of Urban Densification On Outdoor Microclimate And Thermal Comfort Using Envi-Met Simulations For Combined Spatial-Climatic Design (Cscd) Approach, Shreya Banerjee, Rachel X.Y. Pek, Sin Kang Yik, Graces N. Ching, Xiang Tian Ho, Dzyuban Yuliya, Peter J. Crank, Juan A. Acero, Winston T. L. Chow

Research Collection College of Integrative Studies

Future urban planning requires context-specific integration of spatial design and microclimate especially for tropical cities with extreme weather conditions. Thus, we propose a Combined Spatial-Climatic Design approach to assess impact of urban densification on annual outdoor thermal comfort performance employing ENVI-met simulations for Singapore. We first consider building bylaws and residential site guidelines to develop eight urban-density site options for a target population range. We further classify annual weather data into seven weather-types and use them as boundary conditions for the simulations. Comparing such fifty-six combined spatial-climatic simulation outputs by analyzing Outdoor Thermal Comfort Autonomy, we report the influence of …

Value Added Tax Rate Variation, Import Demand And Sectoral Output In Nigeria, Joshua K. Nomkuha, Aondoawase Asooso, Philip T. Abachi

CBN Journal of Applied Statistics (JAS)

This study employs computable general equilibrium (CGE) model to estimate the effect of increase in value added tax (VAT), from 5 per cent to 7.5 per cent, on import demand and sectoral output in Nigeria. The study uses 2020 as the base year for the data analysis. The results show that increase in VAT affects import demand negatively, based on import penetration ratios, with mixed effect across six sectors. The implication of the result is that the VAT policy discourage consumption of foreign products, and constitute excess burden to consumers of such products in Nigeria. The results further reveal that …

Trade Liberalization, Non-Oil Export And Economic Growth In Nigeria, Jerome T. Andohol, Terhemen Tarzoor, Dennis T. Nomor

CBN Journal of Applied Statistics (JAS)

The study examines the impact of trade liberalization and non-oil exports on economic growth in Nigeria from 1986 to 2021. The study utilizes an autoregressive distributed lag model and found the combined effect of trade liberalization and non-oil exports to be positive and statistical significant. While trade liberalization alone may have negative consequences, its synergy with a robust non-oil export can drive sustainable economic growth. The study recommends that strategies to enhance non-oil exports should be encouraged to support the effectiveness of trade liberalization in promoting growth.

The Effectiveness Of Monetary Policy Transmission In Nigeria: Evidence From The Monetary Policy Rate And The Cash Reserve Ratio, Abdulrahman A. Nadani, Auwal Isah

CBN Journal of Applied Statistics (JAS)

This paper investigates the effectiveness of the Monetary Policy Rate (MPR) and Cash Reserve Ratio (CRR) as policy instruments in Nigeria. A structural VAR model is employed to simulate two distinct models measuring shocks from the MPR and the CRR using monthly data from January 2006 to December 2023. Findings show that contractionary monetary policy impulses using MPR and the CRR contract output and credit to the private sector, inflation remains largely positive in the two models, known as the “price puzzle”, but the puzzle is more persistent in the MPR equation. Moreover, shock to MPR strongly influences short-term interest …

Stock Market Volatility In The United Kingdom: Simulating Post-Covid-19 Recovery, Bala A. Dahiru, Mohammed Shuaibu, Najibullah Hassanov

CBN Journal of Applied Statistics (JAS)

This paper investigates the time it would take for the FTSE-100 index to reach its post-COVID-19 peak. The paper utilises an exponential generalised autoregressive conditional heteroscedasticity (EGARCH) model that accounts for leverage effect and asymmetries. The preferred models amongst competing variants was the Autoregressive Moving Average (ARMA)-EGARCH(2,1) specification and was used to predict daily FTSE-100 data from 5th January 2000 to 21st June 2024. The empirical exercise showed that the COVID-19-induced financial crisis negatively affected the United Kingdom’s stock market performance. The results show that the FTSE100 index could reach its post-pandemic peak around 27th August, 2024 (two months after …

Impact Of Fiscal Policy On Financial Inclusion And Development In Nigeria, Okwanya Innocent, Taiwo A. Olusegun, Aimua E. Peace

CBN Journal of Applied Statistics (JAS)

This paper examines the effect of fiscal policy on financial inclusion and development in Nigeria. The study employs the Autoregressive Distributed Lag (ARDL) model and impulse response function (IRF) to determine the extent and response of financial inclusion and development to fiscal policy changes in Nigeria. The study derives a financial inclusion index from three core indicators: access, usage and quality of financial services, while financial development is measured as the ratio of money supply to GDP (M2/GDP). The results show that government expenditure has a significant positive effect on financial inclusion and development, while tax revenue exerts a negative …

How Is Our Mobility Affected As We Age? Findings From A 934 Users Field Study Of Older Adults Conducted In An Urban Asian City, Yi Zhen Tan, Ngoc Doan Thu Tran, Sapphire Lin, Fang Zhao, Yee Sien Ng, Dong Ma, Jeonggil Ko, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

In this paper, we analyze the results of a large study involving 934 older adults living in an urban Asian city that collected their mobility patterns, in the form of logged GPS data, along with a multitude of demographic and health data. We show that mobility, in terms of average distance travelled per day, is greatly affected by age and by employment status. In addition, other factors such as type of day, household size, physical and financial conditions and the onset of retirement also play a significant role in determining the mobility of an individual. These results will have high …

Boring But Demanding: Using Secondary Tasks To Counter The Driver Vigilance Decrement For Partially Automated Driving, Scott Mishler, Jing Chen

Psychology Faculty Publications

Objective

We investigated secondary–task–based countermeasures to the vigilance decrement during a simulated partially automated driving (PAD) task, with the goal of understanding the underlying mechanism of the vigilance decrement and maintaining driver vigilance in PAD.

Background

Partial driving automation requires a human driver to monitor the roadway, but humans are notoriously bad at monitoring tasks over long periods of time, demonstrating the vigilance decrement in such tasks. The overload explanations of the vigilance decrement predict the decrement to be worse with added secondary tasks due to increased task demands and depleted attentional resources, whereas the underload explanations predict the vigilance …

Public Data Resources And Total Factor Productivity Of Enterprises: A Quasi-Natural Experiment Based On Local Government Data Opening, Wuping Wu, Qiheng Li, Liuyi Zhang, Yue Zhao

Research Collection School Of Accountancy

The opening of public data is the government’s major strategic move to release the value of data factor. However, whether these data resources are used by the public to release their value needs to be empirically tested. Therefore, based on the perspective of high-quality development of firms, this paper examines the relation between open public data and firms’ total factor productivity so as to reflect the value of public data resources in driving force of promoting firms’ high-quality development. Taking A-share listed firms from 2010 to 2019 as samples, using a natural experiment based on the launch of the local …

A Thesis, Or Digressions On Sculptural Practice: In Which, Concepts & Influences Thereof Are Explained, Set Forth, Catalogued, Or Divulged By Way Of Commentaries To A Poem, First Conceived By The Artist, Fed Through Chatg.P.T., And Re-Edited By The Artist, To Which Are Added, Annotated References, Impressions And Ruminations Thereof, Also Including Private Thoughts & Personal Accounts Of The Artist, Jaimie An

Masters Theses

This thesis is an exercise in, perhaps a futile, attempt to trace just some of the ideas, stories, and musings I might meander through in my process. It’s not quite a map, nor is it a neat catalogue; it is a haphazard collection of tickets and receipts from a travel abroad, carelessly tossed in a carry-on, only to be stashed upon returning home. These ideas are derived from much greater thinkers and authors than myself; I am a mere collector or a translator, if that, and not a very good one, for much is lost. I do not claim comprehensive …

Fluid Futures: The Revitalization Of Yangzhou Through Its Historical Waterways, Feiyang Wu

Masters Theses

In China, cities such as Yangzhou, which in pre-modern times played central roles in the political, cultural, and economic functioning of the country based on their geographic location, proximity to water-based trade routes, and connections to the imperial court, are today facing uncertain futures due to waterways no longer being critical to trade, and government-driven development being focused on first-tier cities such as Beijing, Shanghai, Shenzhen, and Guangzhou. With this, the working-age population migrates from smaller cities toward these urban giants, leaving behind aging relatives, a less robust and diversified economic base, and few attributes other than cultural tourism that …

Network-Based Representations And Dynamic Discrete Choice Models For Multiple Discrete Choice Analysis, Huy Hung Tran, Tien Mai

Research Collection School Of Computing and Information Systems

In many choice modeling applications, consumer demand is frequently characterized as multiple discrete, which means that consumer choose multiple items simultaneously. The analysis and prediction of consumer behavior in multiple discrete choice situations pose several challenges. In this paper, to address this, we propose a random utility maximization (RUM) based model that considers each subset of choice alternatives as a composite alternative, where individuals choose a subset according to the RUM framework. While this approach offers a natural and intuitive modeling approach for multiple-choice analysis, the large number of subsets of choices in the formulation makes its estimation and application …

Water Management And Conservation In India Fostering Water Justice: Arguing For Adopting Just Sustainability In Water Governance, Gayathri D Naik Dr, Sanjay Shenoi P

Articles

The water sector is characterised by everyday water injustices where factors like social discrimination, economic disparities, and political preferences influence the determination of water resource access, allocation, and management. The increasing anthropogenic impacts on water resources and consequent threats to sustainability add to the water injustices, often impacting the poorer, socially downtrodden communities that bear the brunt of water scarcity and cannot afford alternatives. The current water governance patterns, prioritising equality over equity, fail to address the issues of water injustices created by social, political, and economic factors in water management and sideline the ecological impacts on water resources. Moving …

Financial Time Series Fusion, Completion, And Prediction With Deep Neural Networks, Dan Zhou

Dissertations

Time-series analysis is essential for a wide range of financial applications, including but not limited to bond valuation, firm earnings forecasts, firm fundamentals predictions, and firm characteristics imputations. Given its considerable value, the financial community has shown a strong interest in refining and advancing time-series analysis techniques. The study in this dissertation contributes to this field by employing advanced machine learning approaches, specifically graph neural networks, deep neural networks, and matrix/tensor methods. The primary objectives are twofold: first, to reveal complex correlations within financial time series to improve prediction accuracy, and second, to enhance the process of integrating and imputing …

Try It Together: Transcribing Your Audio With Whisper Api, Bella Ratmelia

2024 AI for Research Week

In this hands-on session, we will explore using the Whisper API to transcribe audio recordings from interviews, focus groups, and speeches. The session will delve into best practices and address common issues that may arise during the transcription process.

Effect Of Social Media On Shaping The Agenda Of The Communicator In The Jordanian Tv Channels, Amer Khaled Ahmad Dr, Hamza Mohammad Nahar, Maram Mohammad Naji Manajreh Dr

Middle East Journal of Communication Studies

The study aimed to assess the extent to which communicators at Jordanian television channels use social media platforms as an information source, and the impact of these platforms on their news and information selection priorities. This was achieved using a survey tool distributed on an equal quota sample of (150) communicators from Jordanian television channels (Jordan TV, AlMamlaka TV, Roya TV). The study found that all the study subjects used social media platforms as a source of information, with the "X platform (formerly Twitter)" being the most used platform. The statement "understanding the audience's interests and preferences to produce tailored …

Risk Factors For Pediatric Ischemic Stroke And Intracranial Hemorrhage: A National Electronic Health Record Based Study, Stuart Fraser, Samantha M Levy, Amee Moreno, Gen Zhu, Sean Savitz, Alicia Zha, Hulin Wu

Faculty, Staff and Student Publications

BACKGROUND: Stroke is an important cause of morbidity in pediatrics. Large studies are needed to better understand the epidemiology, pathogenesis and risk factors associated with pediatric stroke. Large administrative datasets can provide information on risk factors in perinatal and childhood stroke at low cost. The aim of this hypothesis-generating study was to use a large administrative dataset to assess for prevalence and odds-ratios of rare exposures associated with pediatric stroke.

METHODS: The data for patients aged 0-18 with a diagnosis of either ischemic stroke or intracranial hemorrhage were extracted from the Cerner Health Facts EMR Database from 2000 to 2018. …

Baseball Decision-Making: Optimizing At-Bat Simulations, Varun Gopal, Krithika Kondakindi, Nibhrat Lohia, Morgan Williams

SMU Data Science Review

Pitch selection in baseball plays a crucial role, involving pitchers, catchers, and batters working together. This practice, dating back to early baseball, has seen teams try various methods to gain an advantage. This research aims to use reinforcement learning and pitch-by-pitch Statcast data to improve batting strategies. It also builds on previous statistical work (sabermetrics) to make better choices in pitch selection and plate discipline. The dataset used, including over 700,000 pitches for each full season and 200,000 pitches for the COVID-shortened 2020 season, encompasses a wealth of crucial metrics including pitch release point, velocity, and launch angle. This study …

Open Source Supply Chain Security: A Cost-Benefit Analysis Of Achieving Various Security Thresholds In Build Environments, Carly Retterer

Computer Science Senior Theses

Open source software has become a cornerstone of modern software development, offering unparalleled opportunities for innovation and collaboration. However, its widespread adoption has also introduced a host of security vulnerabilities, particularly in the software supply chain. This paper provides a comprehensive cost-benefit analysis of achieving various security thresholds to harden the build environment, focusing on isolated, hermetic, reproducible, and bootstrappable builds. For each build type, we provide a clear definition and outline the steps required for implementation. We then evaluate the associated costs and benefits of each build, emphasizing their roles in strengthening the build environment and enhancing supply chain …

Memories Of Recipes In Twentieth-Century Irish Cookbooks, Gary Thompson

Dublin Gastronomy Symposium

This paper analyses and categorises the ways in which authors and their publishers have chosen to include the author’s culinary, food and personal memories within the texts of twenty twentieth century Irish Cookbooks. Cookbooks are subjects of culinary nostalgia with the reading of a recipe capable of triggering in the reader a memory of a meal enjoyed, a dish cooked in times past by a loved one, or recollections of the disgust felt for a food hated in childhood. Independent from the reader, the culinary memories of the author can be captured at the time of publication in the text …

Academic Search And Discovery Tools In The Age Of Ai And Large Language Models: An Overview Of The Space, Aaron Tay

2024 AI for Research Week

In the ever-evolving landscape of academic research, “AI tools” for literature search and synthesis are currently getting a lot of attention. These tools promise to ramp up productivity, enabling us to accomplish more in less time or absorb more knowledge without drowning in endless reading. With the sheer number of these systems increasing daily, it's natural to wonder: are they really worth our time and money? And if they are, how should we go about picking the right one from the multitude of options?

In this talk, I will share my views on how the space has developed over two …

The Santa Clara, 2024-05-28, Santa Clara University

The Santa Clara

No abstract provided.

Entertainment-Education And Climate Change: Program Examples, Evidence, And Best Practices From Around The World, Suruchi Sood, Amy Henderson Riley, Lyena Birkenstock

College of Population Health Faculty Papers

Entertainment-education is a global theory-driven and evidence-based storytelling strategy that promotes social and behavioral change. A formal review of the peer-reviewed and grey literature, alongside consultations with program and industry experts, revealed several contemporary examples of entertainment-education and climate change. Late-night comedy, with the inclusion of climate change storylines within popular entertainment, is common in the Global North. In the Global South, climate adaptation and mitigation narratives are situated in formats portraying audiences’ lived experiences. Crosscutting trends relate to documentary storytelling, children’s programming, and future efforts. Recommendations include re-examining theories across the social-ecological model; placing entertainment front and center; including …

Examining Differences In Concept Representation Across Similarity Spaces Between Humans And Large Language Models, Krishnachandra Nair

Computer Science Senior Theses

The replication of human concept representation is a critical task for the pursuit of artificial general intelligence. With the recent influx of large language models that demonstrate text-generation capabilities nearly on par with humans, the question stands on whether these large language models can capture concepts within language. We examine this question by exploring differences in concept representation across similarity spaces between humans and LLMs. We find that, while concept representation within LLMs does partially mimic human concept representation, LLMs are greatly limited by their dependence on semantic information and cannot therefore develop an understanding of human social code or …

Ripl: Recursive Inference For Policy Learning, Kunal Jha, Jeremy R. Manning, Alberto Quattrini Li

Computer Science Senior Theses

Humans excel at understanding the thoughts and intentions of others (theory of mind) and leverage this ability to learn and adapt in social environments. However, replicating this capability in artificial agents remains a challenge. This paper explores the gap between fast, efficient learning often achieved by Reinforcement Learning (RL) algorithms and the interpretability and adaptability desired in agents interacting with humans. We propose a novel approach that integrates an inference network within existing RL frameworks. This allows agents to reason about the beliefs of others (nested reasoning) while learning optimal actions. Our method leverages approximate solutions to the I-POMDP framework, …

Comparing Researchers’ Degree Of Dichotomous Thinking Using Frequentist Versus Bayesian Null Hypothesis Testing, Jasmine Muradchanian, Rink Hoekstra, Henk Kiers, Dustin Fife, Don Van Ravenzwaaij

College of Science & Mathematics Departmental Research

A large amount of scientific literature in social and behavioural sciences bases their conclusions on one or more hypothesis tests. As such, it is important to obtain more knowledge about how researchers in social and behavioural sciences interpret quantities that result from hypothesis test metrics, such as p-values and Bayes factors. In the present study, we explored the relationship between obtained statistical evidence and the degree of belief or confidence that there is a positive effect in the population of interest. In particular, we were interested in the existence of a so-called cliff effect: A qualitative drop in the …