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Articles 1 - 13 of 13
Full-Text Articles in Data Science
On The Exactitude Of Big Data: La Bêtise And Artificial Intelligence, Noel Fitzpatrick, John D. Kelleher
On The Exactitude Of Big Data: La Bêtise And Artificial Intelligence, Noel Fitzpatrick, John D. Kelleher
Articles
This article revisits the question of ‘la bêtise’ or stupidity in the era of Artificial Intelligence driven by Big Data, it extends on the questions posed by Gille Deleuze and more recently by Bernard Stiegler. However, the framework for revisiting the question of la bêtise will be through the lens of contemporary computer science, in particular the development of data science as a mode of analysis, sometimes, misinterpreted as a mode of intelligence. In particular, this article will argue that with the advent of forms of hype (sometimes referred to as the hype cycle) in relation to big data and …
Relationships Between Social Network Characteristics, Alcohol Use, And Alcohol-Related Consequences In A Large Network Of First-Year College Students: How Do Peer Drinking Norms Fit In?, Graham T. Diguiseppi, Matthew K. Meisel, Sara G. Balestrieri, Miles Q. Ott, Melissa A. Clark, Nancy P. Barnett
Relationships Between Social Network Characteristics, Alcohol Use, And Alcohol-Related Consequences In A Large Network Of First-Year College Students: How Do Peer Drinking Norms Fit In?, Graham T. Diguiseppi, Matthew K. Meisel, Sara G. Balestrieri, Miles Q. Ott, Melissa A. Clark, Nancy P. Barnett
Statistical and Data Sciences: Faculty Publications
A burgeoning area of research is using social network analysis to investigate college students' substance use behaviors. However, little research has incorporated students' perceived peer drinking norms into these analyses. The present study investigated the association between social network characteristics, alcohol use, and alcohol-related consequences among first-year college students (N 1,342; 81% of the first-year class) at one university. The moderating role of descriptive norms was also examined. Network characteristics and descriptive norms were derived from participants' nominations of up to 10 other students who were important to them; individual network characteristics included popularity (indegree), network expansiveness (outdegree), relationship reciprocity, …
Non-Manual Articulators In Irish Sign Language Verbs: An Analysis With Data Mining Association Rules, Robert G. Smith, Markus Hofmann
Non-Manual Articulators In Irish Sign Language Verbs: An Analysis With Data Mining Association Rules, Robert G. Smith, Markus Hofmann
Conference Papers
The Signs of Ireland (SOI) corpus (Leeson et al., 2006) deploys a complex multi-tiered temporal data structure. The process of manually analyzing such data is laborious, cannot eliminate bias and often, important patterns can go completely unnoticed. In addition to this, as a result of the complex nature of grammatical structures contained in the corpus, identifying complex linguistic associations or patterns across tiers is simply too intricate a task for a human to carry out in an acceptable timeframe. This work explores the application of data mining techniques on a set of multi-tiered temporal data from the SOI corpus. Building …
Strategic Players For Identifying Optimal Social Network Intervention Subjects, Miles Q. Ott, John M. Light, Melissa A. Clark, Nancy P. Barnett
Strategic Players For Identifying Optimal Social Network Intervention Subjects, Miles Q. Ott, John M. Light, Melissa A. Clark, Nancy P. Barnett
Statistical and Data Sciences: Faculty Publications
We present a method whereby social network ties are used to identify behavioral leaders who are situated in the network such that these individuals are: 1) able to influence other individuals who are in need of and most receptive to intervention, thereby optimizing the impact of the intervention; and 2) not embedded with ties to individuals that are likely to be behaviorally antagonistic to the intervention or that would compromise the optimal impact of intervention. In this study we developed a method that we call Strategic Players, which is a solution for identifying a set of players who are close …
Potential For Participatory Big Data Ethics And Algorithm Design: A Scoping Mapping Review, Madisson Whitman, Chien-Yi Hsiang, Kendall Roark
Potential For Participatory Big Data Ethics And Algorithm Design: A Scoping Mapping Review, Madisson Whitman, Chien-Yi Hsiang, Kendall Roark
Libraries Faculty and Staff Scholarship and Research
Ubiquitous networked data collection and algorithm-based information systems have the potential to disparately impact lives around the planet and pose a host of emerging ethical challenges. One response has been a call for more transparency and democratic control over the design and implementation of such systems. This scoping mapping review focuses on participatory approaches to the design, governance, and future of these systems across a wide variety of contexts and domains.
Simplicity And Sustainability: Pointers From Ethics And Science, Mehrdad Massoudi, Ashwin Vaidya
Simplicity And Sustainability: Pointers From Ethics And Science, Mehrdad Massoudi, Ashwin Vaidya
Department of Mathematics Facuty Scholarship and Creative Works
In this paper, we explore the notion of simplicity. We use definitions of simplicity proposed by philosophers, scientists, and economists. In an age when the rapidly growing human population faces an equally rapidly declining energy/material resources, there is an urgent need to consider various notions of simplicity, collective and individual, which we believe to be a sensible path to restore our planet to a reasonable state of health. Following the logic of mathematicians and physicists, we suggest that simplicity can be related to sustainability. Our efforts must therefore not be spent so much in pursuit of growth but in achieving …
Deep Learning For Multisensor Image Resolution Enhancement, Charles B. Collins, John M. Beck, Susan M. Bridges, John A. Rushing
Deep Learning For Multisensor Image Resolution Enhancement, Charles B. Collins, John M. Beck, Susan M. Bridges, John A. Rushing
Research Horizons Day Posters
No abstract provided.
Multi-Point Vibration Measurement And Mode Magnification Of Civil Structures Using Video-Based Motion Processing, Zhexiong Shang, Zhigang Shen
Multi-Point Vibration Measurement And Mode Magnification Of Civil Structures Using Video-Based Motion Processing, Zhexiong Shang, Zhigang Shen
Department of Construction Engineering and Management: Faculty Publications
Image-based vibration measurement has gained increased attentions in civil and construction communities. A recent video-based motion magnification method was developed to measure and visualize small structure motions. This new approach presents a potential for low-cost vibration measurement and mode shape identification. Pilot studies using this approach on simple rigid body structures were reported. Its validity on complex outdoor structures has not been investigated. In this study, a non-contact video-based approach for multi-point vibration measurement and mode magnification is introduced. The proposed approach can output a full-field vibration map that increases the efficiency of the current structural health monitoring (SHM) practice. …
A Mathematical Analysis Of The Game Of Chess, John C. White
A Mathematical Analysis Of The Game Of Chess, John C. White
Selected Honors Theses
This paper analyzes chess through the lens of mathematics. Chess is a complex yet easy to understand game. Can mathematics be used to perfect a player’s skills? The work of Ernst Zermelo shows that one player should be able to force a win or force a draw. The work of Shannon and Hardy demonstrates the complexities of the game. Combinatorics, probability, and some chess puzzles are used to better understand the game. A computer program is used to test a hypothesis regarding chess strategy. Through the use of this program, we see that it is detrimental to be the first …
Summary Of The Special Issue “Neutrosophic Information Theory And Applications” At “Information” Journal, Florentin Smarandache, Jun Ye
Summary Of The Special Issue “Neutrosophic Information Theory And Applications” At “Information” Journal, Florentin Smarandache, Jun Ye
Branch Mathematics and Statistics Faculty and Staff Publications
Over a period of seven months (August 2017–February 2018), the Special Issue dedicated to “Neutrosophic Information Theory and Applications” by the “Information” journal (ISSN 2078-2489), located in Basel, Switzerland, was a success. The Guest Editors, Prof. Dr. Florentin Smarandache from the University of New Mexico (USA) and Prof. Dr. Jun Ye from the Shaoxing University (China), were happy to select—helped by a team of neutrosophic reviewers from around the world, and by the “Information” journal editors themselves—and publish twelve important neutrosophic papers, authored by 27 authors and coauthors. There were a variety of neutrosophic topics studied and used by the …
Compression And Relaxation Of Fishing Effort In Response To Changes In Length Of Fishing Season For Red Snapper (Lutjanus Campechanus) In The Northern Gulf Of Mexico, Sean P. Powers, Kevin Anson
Compression And Relaxation Of Fishing Effort In Response To Changes In Length Of Fishing Season For Red Snapper (Lutjanus Campechanus) In The Northern Gulf Of Mexico, Sean P. Powers, Kevin Anson
University Faculty and Staff Publications
A standard method used by fisheries managers to decrease catch and effort is to shorten the length of a fishery; however, data on recreational angler response to this simple approach are surprisingly lacking. We assessed the effect of variable season length on daily fishing effort, measured by using numbers of boat launches per day, anglers per boat, and anglers per day from video observations, in the recreational sector of the federal fishery for red snapper (Lutjanus campechanus) in coastal Alabama. From 2012 through 2017, season length fluctuated from 3 to 40 d. Daily effort, measured by using mean number of …
Non-Linear Machine Learning With Active Sampling For Mox Drift Compensation, Tamara Matthews, Muhammad Iqbal, Horacio Gonzalez-Velez
Non-Linear Machine Learning With Active Sampling For Mox Drift Compensation, Tamara Matthews, Muhammad Iqbal, Horacio Gonzalez-Velez
Conference papers
Abstract—Metal oxide (MOX) gas detectors based on SnO2 provide low-cost solutions for real-time sensing of complex gas mixtures for indoor ambient monitoring. With high sensitivity under ideal conditions, MOX detectors may have poor longterm response accuracy due to environmental factors (humidity and temperature) along with sensor aging, leading to calibration drifts. Finding a simple and efficient solution to correct such calibration drifts has been the subject of numerous studies but remains an open problem. In this work, we present an efficient approach to MOX calibration using active and transfer sampling techniques coupled with non-linear machine learning algorithms, namely neural networks, …
Estimating Exploitation Rates In The Alabama Red Snapper Fishery Using A High-Reward Tag–Recapture Approach, Dana K. Sackett, Mattgew Catalano, J. Marcus Drymon, Sean P. Powers, Mark Albins
Estimating Exploitation Rates In The Alabama Red Snapper Fishery Using A High-Reward Tag–Recapture Approach, Dana K. Sackett, Mattgew Catalano, J. Marcus Drymon, Sean P. Powers, Mark Albins
University Faculty and Staff Publications
Accurate estimates of exploitation are essential to managing an exploited fishery. However, these estimates are often dependent on the area and vulnerable sizes of fish considered in a study. High-reward tagging studies offer a simple and direct approach to estimating exploitation rates at these various scales and in examining how model parameters impact exploitation rate estimates. These methods can ultimately provide a better understanding of the spatial dynamics of exploitation at smaller local and regional scales within a fishery—a measure often needed for more site-attached species, such as the Red Snapper Lutjanus campechanus. We used this approach to tag 724 …