Physical Sciences and Mathematics Commons^™

Ethical Data Considerations For Engaging In Reparative Archival Practice, Jamie Rogers, Rhia Rae

Works of the FIU Libraries

Archival textually-rich materials--such as warranty deeds, mortgages, legal documents, and letter correspondence--can provide valuable historical insights, and if transcribed and analyzed, can produce data points in the form of unstructured text, tabular data, and geospatial assets. This presentation will provide an overview of the process Florida International University librarians went through to turn the papers of Dana A. Dorsey, Miami's first Black Millionaire, into data. Their work is guided by the concept of "collections as data" as a form of reparative archival practice, enabling the elevation of marginalized individuals' histories. The goal of reparative archival practice is to create a …

Data Ethics And Privacy For Researchers, Kelley F. Rowan

Works of the FIU Libraries

This workshop addresses specific data privacy and anonymization standards and techniques for researchers that are collecting personally identifiable information as well as sensitive information. The workshop covers federal, state, and international laws and regulations governing data privacy, the development of an impact assessment and privacy policy. The second half of the workshop focuses on ethical workflows, anonymization techniques and related resources.

Produção De Artigos Científicos No Estudo Longitudinal De Saúde Do Adulto (Elsa-Brasil), 2011-2023, Arthur Sandi Bauermann, Maria Antônia Mylius De Oliveira, Clara Akemi Basso Aseka, Luiza Dalmolin Beneduzi

AMNET XX Conferencia Internacional

No abstract provided.

“I Think I Discovered A Military Base In The Middle Of The Ocean”—Null Island, The Most Real Of Fictional Places, Levente Juhasz, Peter Mooney

GIS Center

This paper explores Null Island, a fictional place located at 0° latitude and 0° longitude in the WGS84 (World Geodetic System 1984) geographic coordinate system. Null Island is erroneously associated with large amounts of geographic data in a wide variety of location-based services, place databases, social media and web-based maps. Whereas it was originally considered a joke within the geospatial community, this article will demonstrate implications of its existence, both technological and social in nature, promoting Null Island as a fundamental issue of geographic information that requires more widespread awareness. The article summarizes error sources that lead to data being …

A Bayesian Programming Approach To Car-Following Model Calibration And Validation Using Limited Data, Franklin Abodo

FIU Electronic Theses and Dissertations

Traffic simulation software is used by transportation researchers and engineers to design and evaluate changes to roadway networks. Underlying these simulators are mathematical models of microscopic driver behavior from which macroscopic measures of flow and congestion can be recovered. Many models are intended to apply to only a subset of possible traffic scenarios and roadway configurations, while others do not have any explicit constraint on their applicability. Work zones on highways are one scenario for which no model invented to date has been shown to accurately reproduce realistic driving behavior. This makes it difficult to optimize for safety and other …

Anomaly Detection In Sequential Data: A Deep Learning-Based Approach, Jayesh Soni

FIU Electronic Theses and Dissertations

Anomaly Detection has been researched in various domains with several applications in intrusion detection, fraud detection, system health management, and bio-informatics. Conventional anomaly detection methods analyze each data instance independently (univariate or multivariate) and ignore the sequential characteristics of the data. Anomalies in the data can be detected by grouping the individual data instances into sequential data and hence conventional way of analyzing independent data instances cannot detect anomalies. Currently: (1) Deep learning-based algorithms are widely used for anomaly detection purposes. However, significant computational overhead time is incurred during the training process due to static constant batch size and learning …

Intelligent Data Analytics Using Deep Learning For Data Science, Maria E. Presa Reyes

FIU Electronic Theses and Dissertations

Nowadays, data science stimulates the interest of academics and practitioners because it can assist in the extraction of significant insights from massive amounts of data. From the years 2018 through 2025, the Global Datasphere is expected to rise from 33 Zettabytes to 175 Zettabytes, according to the International Data Corporation. This dissertation proposes an intelligent data analytics framework that uses deep learning to tackle several difficulties when implementing a data science application. These difficulties include dealing with high inter-class similarity, the availability and quality of hand-labeled data, and designing a feasible approach for modeling significant correlations in features gathered from …

Osm Science - The Academic Study Of The Openstreetmap Project, Data, Contributors, Community, And Applications, A. Yair Grinberger, Marco Minghini, Levente Juhasz, Godwin Yeboah, Peter Mooney

GIS Center

This paper is an Editorial for the Special Issue titled “OpenStreetMap as a multidisciplinary nexus: perspectives, practices and procedures”. The Special Issue is largely based on the talks presented in the 2019 and 2020 editions of the Academic Track at the State of the Map conferences. As such, it represents the most pressing and relevant issues and topics considered by the academic community in relation to OpenStreetMap (OSM)—a global project and community aimed to create and maintain a free and editable database and map of the world. In this Editorial, we survey the papers included in the Special Issue, grouping …

A Machine Learning Framework For Identifying Molecular Biomarkers From Transcriptomic Cancer Data, Md Abdullah Al Mamun

FIU Electronic Theses and Dissertations

Cancer is a complex molecular process due to abnormal changes in the genome, such as mutation and copy number variation, and epigenetic aberrations such as dysregulations of long non-coding RNA (lncRNA). These abnormal changes are reflected in transcriptome by turning oncogenes on and tumor suppressor genes off, which are considered cancer biomarkers.

However, transcriptomic data is high dimensional, and finding the best subset of genes (features) related to causing cancer is computationally challenging and expensive. Thus, developing a feature selection framework to discover molecular biomarkers for cancer is critical.

Traditional approaches for biomarker discovery calculate the fold change for each …

Volitional Control Of Lower-Limb Prosthesis With Vision-Assisted Environmental Awareness, S M Shafiul Hasan

FIU Electronic Theses and Dissertations

Early and reliable prediction of user’s intention to change locomotion mode or speed is critical for a smooth and natural lower limb prosthesis. Meanwhile, incorporation of explicit environmental feedback can facilitate context aware intelligent prosthesis which allows seamless operation in a variety of gait demands. This dissertation introduces environmental awareness through computer vision and enables early and accurate prediction of intention to start, stop or change speeds while walking. Electromyography (EMG), Electroencephalography (EEG), Inertial Measurement Unit (IMU), and Ground Reaction Force (GRF) sensors were used to predict intention to start, stop or increase walking speed. Furthermore, it was investigated whether …

Bridges And Barriers: An Exploration Of Engagements Of The Research Community With The Openstreetmap Community, A. Yair Grinberger, Marco Minghini, Godwin Yeboah, Levente Juhasz, Peter Mooney

GIS Center

The academic community frequently engages with OpenStreetMap (OSM) as a data source and research subject, acknowledging its complex and contextual nature. However, existing literature rarely considers the position of academic research in relation to the OSM community. In this paper we explore the extent and nature of engagement between the academic research community and the larger communities in OSM. An analysis of OSM-related publications from 2016 to 2019 and seven interviews conducted with members of one research group engaged in OSM-related research are described. The literature analysis seeks to uncover general engagement patterns while the interviews are used to identify …

Towards Understanding The Temporal Accuracy Of Openstreetmap: A Quantitative Experiment, Levente Juhasz

GIS Center

No abstract provided.

Interpretability Of Ai In Computer Systems And Public Policy, Farzana Beente Yusuf

FIU Electronic Theses and Dissertations

Advances in Artificial Intelligence (AI) have led to spectacular innovations and sophisticated systems for tasks that were thought to be capable only by humans. Examples include playing chess and Go, face and voice recognition, driving vehicles, and more. In recent years, the impact of AI has moved beyond offering mere predictive models into building interpretable models that appeal to human logic and intuition because they ensure transparency and simplicity and can be used to make meaningful decisions in real-world applications. A second trend in AI is characterized by important advancements in the realm of causal reasoning. Identifying causal relationships is …

Reimagining The Archive For Computational Analysis At Scale, Jamie Rogers

Works of the FIU Libraries

This presentation was part of a three-segment panel discussion sponsored by IS&T, the Society for Imaging Science and Technology, titled "OCR and Text Recognition: Workflows, Trends, and New Applications." This segment covers ways in which we have re-conceptualized archive materials as computationally useful data as well as the value of utilizing data at scale to impact research possibilities. We have been able to accomplish this through an ongoing project "dLOC as Data: A Thematic Approach to Caribbean Newspapers," a collaborative initiative between the Digital Library of the Caribbean, University of Florida, and Florida International University.

Collections As Data At Florida International University, Jamie Rogers

Works of the FIU Libraries

This presentation provides an overview of the concept of collections as data; shares information about our "dLOC as Data" grant initiative, a collaboration between the Digital Library of the Caribbean (dLOC), the Florida International University (FIU) Libraries Digital Collections Center, and the University of Florida Libraries, funded by the Mellon sub-award program, "Collections as Data: Part to Whole" ; as well as provides an opportunity to talk about how we can share more collections as data resources and undertake new and exciting projects at FIU.

Although the concept of collections as data isn't new, it is becoming more mainstream. As …

Evaluation Of Parametric And Nonparametric Statistical Models In Wrong-Way Driving Crash Severity Prediction, Sajidur Rahman Nafis

FIU Electronic Theses and Dissertations

Wrong-way driving (WWD) crashes result in more fatalities per crash, involve more vehicles, and cause extended road closures compared to other types of crashes. Although crashes involving wrong-way drivers are relatively few, they often lead to fatalities and serious injuries. Researchers have been using parametric statistical models to identify factors that affect WWD crash severity. However, these parametric models are generally based on several assumptions, and the results could generate numerous errors and become questionable when these assumptions are violated. On the other hand, nonparametric methods such as data mining or machine learning techniques do not use a predetermined functional …

Correlating Water Quality And Profile Data In The Florida Keys Using Machine Learning Methods, Alejandro M. Torres Castellanos

FIU Electronic Theses and Dissertations

Water quality is a very active subject of research in the water science field, where its importance includes maintaining the environment, managing wastewater, and securing fresh water. However, the increase of human development has led to problems that are affecting the ecosystem. Motivated by these problems, this research aims to find a solution for understanding the coastal water of the Florida Keys. The research used machine learning methods to find a correlation between water quality dataset and profile measurements dataset. To achieve this objective, the research first went through cleaning, rescuing, and structuring a readable dataset of the profile measurements …

An Angle-Based Stochastic Gradient Descent Method For Machine Learning: Principle And Application, Chongya Song

FIU Electronic Theses and Dissertations

In deep learning, optimization algorithms are employed to expedite the resolution to accurate models through the calibrations of the current gradient and the associated learning rate. A major shortcoming of these existing methods is the manner in which the calibration terms are computed, only utilizing the previous gradients during their computations. Because the gradient is a time-sensitive variable computed at a specific moment in time, it is possible that older gradients can introduce significant deviation into the calibration terms. Although most algorithms alleviate this situation by combining the exponential moving average of the previous gradients, we found that this method …

Causality In Microbiomes, Md Musfiqur Rahman Sazal

FIU Electronic Theses and Dissertations

No abstract provided.

3d Architectural Analysis Of Neurons, Astrocytes, Vasculature & Nuclei In The Motor And Somatosensory Murine Cortical Columns, Jared Leichner

FIU Electronic Theses and Dissertations

Characterization of the complex cortical structure of the brain at a cellular level is a fundamental goal of neuroscience which can provide a better understanding of both normal function as well as disease state progression. Many challenges exist however when carrying out this form of analysis. Immunofluorescent staining is a key technique for revealing 3-dimensional structure, but subsequent fluorescence microscopy is limited by the quantity of simultaneous targets that can be labeled and intrinsic lateral and isotropic axial point-spread function (PSF) blurring during the imaging process in a spectral and depth-dependent manner. Even after successful staining, imaging and optical deconvolution, …