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Articles 781 - 810 of 983

Full-Text Articles in Artificial Intelligence and Robotics

Accessibility Of Deepfakes, Andrew L. Collings Jan 2020

Accessibility Of Deepfakes, Andrew L. Collings

Cybersecurity Undergraduate Research Showcase

The danger posed by falsified media, commonly referred to as deepfakes, has been well researched and documented. The software Faceswap to was used to swap the faces of two politician (Joe Biden and Donald Trump). The testing was performed using an affordable consumer GPU (an AMD Radeon RX 570) over 100,000 iterations. The process and results for the two attempts with the best results (and largest differences) were recorded. The result was ultimately unconvincing, while the software was able to recreate the facial structure the lighting and skin tone did not blend at all.

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Customer And Employee Social Media Comments/Feedback And Stock Purchasing Decisions Enhanced By Sentiment Analysis, Drew Mikel Hall Jan 2020

Customer And Employee Social Media Comments/Feedback And Stock Purchasing Decisions Enhanced By Sentiment Analysis, Drew Mikel Hall

Walden Dissertations and Doctoral Studies

The U.S. Securities and Exchange Commission (SEC) warns professional investors that sentiment analysis tools may lead to impulsive investment decision-making. This warning comes despite evidence showing that aided social sentiment investment decision tools can increase accurate investment decision-making by 18%. Using Fama's theory of efficient market hypothesis, the purpose of this quantitative correlational study was to examine whether customer Twitter comments and employee Glassdoor feedback sentiment predicted successful investing decisions measured by business stock prices. Two thousand records from 3 archival U.S. public NASDAQ 100 datasets from March 28, 2016, to June 15, 2016 (79 days) of 53 companies with …

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Exploring Artificial Intelligence-Mediated Communication (Aimc) As A Sub-Field Of Communication Studies. A Textual Examination, Md Nurul Karim Bhuiyan Jan 2020

Exploring Artificial Intelligence-Mediated Communication (Aimc) As A Sub-Field Of Communication Studies. A Textual Examination, Md Nurul Karim Bhuiyan

All Graduate Theses, Dissertations, and Other Capstone Projects

From the book "Speaking into the Air: A History of the Idea of Communication," written by John Durham Peters, we understand a notion about developing one’s destiny; people have the freedom to choose multiple paths to follow (Peters, 2012). If we reject this idea, it is also easy for people to come up with distinct explanations. Even though the meaning of the same issues might vary subject to who is interpreting them, the primary concepts can be interpreted as more or less the same. If we study these two--"artificial intelligence" and "communication"- simultaneously, we can assume some characteristics. Thus, this …

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Artificial Intelligence-Enhanced Decision Support For Informing Global Sustainable Development: A Human-Centric Ai-Thinking Approach, Meng-Leong How, Sin Mei Cheah, Yong-Jiet Chan, Aik Cheow Khor, Eunice Mei Ping Say Jan 2020

Artificial Intelligence-Enhanced Decision Support For Informing Global Sustainable Development: A Human-Centric Ai-Thinking Approach, Meng-Leong How, Sin Mei Cheah, Yong-Jiet Chan, Aik Cheow Khor, Eunice Mei Ping Say

CCX Research

Sustainable development is crucial to humanity. Utilization of primary socio-environmental data for analysis is essential for informing decision making by policy makers about sustainability in development. Artificial intelligence (AI)-based approaches are useful for analyzing data. However, it was not easy for people who are not trained in computer science to use AI. The significance and novelty of this paper is that it shows how the use of AI can be democratized via a user-friendly human-centric probabilistic reasoning approach. Using this approach, analysts who are not computer scientists can also use AI to analyze sustainability-related EPI data. Further, this human-centric probabilistic …

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Law, Artificial Intelligence, And Natural Language Processing: A Funny Thing Happened On The Way To My Search Results, Paul D. Callister Jan 2020

Law, Artificial Intelligence, And Natural Language Processing: A Funny Thing Happened On The Way To My Search Results, Paul D. Callister

Faculty Works

Renowned legal educator Roscoe Pound stated, “Law must be stable and yet it cannot stand still.” Yet, as Susan Nevelow Mart has demonstrated in a seminal article that the different online research services (Westlaw, Lexis Advance, Fastcase, Google Scholar, Ravel and Casetext) produce significantly different results when researching case law. Furthermore, a recent study of 325 federal courts of appeals decisions, revealed that only 16% of the cases cited in appellate briefs make it into the courts’ opinions. This does not exactly inspire confidence in legal research or its tools to maintain stability of the law. As Robert Berring foresaw, …

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Shipbuilding Supply Chain Framework And Digital Transformation: A Project Portfolios Risk Evaluation, Rafael Diaz, Katherine Smith, Rafael Landaeta, Antonio Padovano Jan 2020

Shipbuilding Supply Chain Framework And Digital Transformation: A Project Portfolios Risk Evaluation, Rafael Diaz, Katherine Smith, Rafael Landaeta, Antonio Padovano

VMASC Publications

Program portfolio managers in digital transformation programs have a need for knowledge that can guide decisions related to the alignment of program investments with the sustainability and strategic objectives of the organization. The purpose of this research is to illustrate the utility of a framework capable of clarifying the cost-benefit tradeoffs stemming from assessing digitalization program investment risks in the military shipbuilding sector. Our approach uses Artificial Neural Network to quantify benefits and risks per project while employing scenario analysis to quantify the effects of operational constraints. A Monte Carlo model is used to generate data samples that support the …

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Interpreting Health Events In Big Data Using Qualitative Traditions, Roschelle L. Fritz, Gordana Dermody Jan 2020

Interpreting Health Events In Big Data Using Qualitative Traditions, Roschelle L. Fritz, Gordana Dermody

Research outputs 2014 to 2021

© The Author(s) 2020. The training of artificial intelligence requires integrating real-world context and mathematical computations. To achieve efficacious smart health artificial intelligence, contextual clinical knowledge serving as ground truth is required. Qualitative methods are well-suited to lend consistent and valid ground truth. In this methods article, we illustrate the use of qualitative descriptive methods for providing ground truth when training an intelligent agent to detect Restless Leg Syndrome. We show how one interdisciplinary, inter-methodological research team used both sensor-based data and the participant’s description of their experience with an episode of Restless Leg Syndrome for training the intelligent agent. …

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Estimating Free-Flow Speed With Lidar And Overhead Imagery, Armin Hadzic Jan 2020

Estimating Free-Flow Speed With Lidar And Overhead Imagery, Armin Hadzic

Theses and Dissertations--Computer Science

Understanding free-flow speed is fundamental to transportation engineering in order to improve traffic flow, control, and planning. The free-flow speed of a road segment is the average speed of automobiles unaffected by traffic congestion or delay. Collecting speed data across a state is both expensive and time consuming. Some approaches have been presented to estimate speed using geometric road features for certain types of roads in limited environments. However, estimating speed at state scale for varying landscapes, environments, and road qualities has been relegated to manual engineering and expensive sensor networks. This thesis proposes an automated approach for estimating free-flow …

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Deep Learning For Overhead Imagery: Algorithms And Applications, Anthony Manuel Ortiz Cepeda Jan 2020

Deep Learning For Overhead Imagery: Algorithms And Applications, Anthony Manuel Ortiz Cepeda

Open Access Theses & Dissertations

Remote sensing using overhead imagery has critical impact to the way we understand our environment and offers crucial information for scene understanding, climate change research, disaster response, urban planning, forest management, and many other applications. At present, deep learning is increasingly used in remote sensing, but mostly borrowing algorithms developed for natural images in the computer vision community. Specific challenges arise while applying deep learning to remote sensing. These challenges include issues related to the high dimensionality and limited labeled data, security and robustness to adversarial attacks, and model generalization. In this Thesis we focus on tackling these key challenges. …

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Could A Robot Be Your Psychotherapist?, Benjamin Huston Jan 2020

Could A Robot Be Your Psychotherapist?, Benjamin Huston

Graduate School of Professional Psychology: Doctoral Papers and Masters Projects

As technology has advanced over the years, it has been integrated into psychotherapy and changed the way that people receive mental health care (Schopp, Demiris, & Glueckauf, 2006). Many of these advances, such as telehealth practices, were seen as unsustainable until the public Internet offered broader access to technology-based care in the 1990s (Schopp, Demiris, & Glueckauf, 2006). These technology-based practices have since grown in popularity and with a recent increase in telehealth practices, text-based therapies, and applications to aid in mental health practices, modern therapy looks very different than it did even ten years ago (Fiske, Henningsen, & Buyx, …

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Implementation Considerations For Mitigating Bias In Supervised Machine Learning, Bardia Bijani Aval Jan 2020

Implementation Considerations For Mitigating Bias In Supervised Machine Learning, Bardia Bijani Aval

CSB and SJU Distinguished Thesis

Machine Learning (ML) is an important component of computer science and a mainstream way of making sense of large amounts of data. Although the technology is establishing new possibilities in different fields, there are also problems to consider, one of which is bias. Due to the inductive reasoning of ML algorithms in creating mathematical models, the predictions and trends found by the models will never necessarily be true – just more or less probable. Knowing this, it is unreasonable for us to expect the applied deductive reasoning of these models to ever be fully unbiased. Therefore, it is important that …

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Fast Decision-Making Under Time And Resource Constraints, Kyle Gabriel Lassak Jan 2020

Fast Decision-Making Under Time And Resource Constraints, Kyle Gabriel Lassak

Graduate Theses, Dissertations, and Problem Reports (ETD)

Practical decision makers are inherently limited by computational and memory resources as well as the time available in which to make decisions. To cope with these limitations, humans actively seek methods which limit their resource demands by exploiting structure within the environment and exploiting a coupling between their sensing and actuation to form heuristics for fast decision-making. To date, such behavior has not been replicated in artificial agents. This research explores how heuristics may be incorporated into the decision-making process to quickly make high-quality decisions through the analysis of a prominent case study: the outfielder problem. In the outfielder problem, …

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Opening Books And The National Corpus Of Graduate Research, William A. Ingram, Edward A. Fox, Jian Wu Jan 2020

Opening Books And The National Corpus Of Graduate Research, William A. Ingram, Edward A. Fox, Jian Wu

Computer Science Faculty Publications

Virginia Tech University Libraries, in collaboration with Virginia Tech Department of Computer Science and Old Dominion University Department of Computer Science, request $505,214 in grant funding for a 3-year project, the goal of which is to bring computational access to book-length documents, demonstrating that with Electronic Theses and Dissertations (ETDs). The project is motivated by the following library and community needs. (1) Despite huge volumes of book-length documents in digital libraries, there is a lack of models offering effective and efficient computational access to these long documents. (2) Nationwide open access services for ETDs generally function at the metadata level. …

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An Ai Approach To Measuring Financial Risk, Lining Yu, Wolfgang Karl Hardle, Lukas Borke, Thijs Benschop Dec 2019

An Ai Approach To Measuring Financial Risk, Lining Yu, Wolfgang Karl Hardle, Lukas Borke, Thijs Benschop

Sim Kee Boon Institute for Financial Economics

AI artificial intelligence brings about new quantitative techniques to assess the state of an economy. Here, we describe a new measure for systemic risk: the Financial Risk Meter (FRM). This measure is based on the penalization parameter (λ" role="presentation" style="box-sizing: border-box; display: inline; font-style: normal; font-weight: normal; line-height: normal; font-size: 18px; text-indent: 0px; text-align: left; text-transform: none; letter-spacing: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative;">λλ) of a linear quantile lasso regression. The FRM is calculated by taking the average …

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A Mathematical Programming Model For The Green Mixed Fleet Vehicle Routing Problem With Realistic Energy Consumption And Partial Recharges, Vincent F. Yu, Panca Jodiwan, Aldy Gunawan, Audrey Tedja Widjaja Dec 2019

A Mathematical Programming Model For The Green Mixed Fleet Vehicle Routing Problem With Realistic Energy Consumption And Partial Recharges, Vincent F. Yu, Panca Jodiwan, Aldy Gunawan, Audrey Tedja Widjaja

Research Collection School Of Computing and Information Systems

A green mixed fleet vehicle routing with realistic energy consumption and partial recharges problem (GMFVRP-REC-PR) is addressed in this paper. This problem involves a fixed number of electric vehicles and internal combustion vehicles to serve a set of customers. The realistic energy consumption which depends on several variables is utilized to calculate the electricity consumption of an electric vehicle and fuel consumption of an internal combustion vehicle. Partial recharging policy is included into the problem to represent the real life scenario. The objective of this problem is to minimize the total travelled distance and the total emission produced by internal …

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“Where’S The I-O?” Artificial Intelligence And Machine Learning In Talent Management Systems, Manuel F. Gonzalez, John F. Capman, Frederick L. Oswald, Evan R. Theys, David L. Tomczak Nov 2019

“Where’S The I-O?” Artificial Intelligence And Machine Learning In Talent Management Systems, Manuel F. Gonzalez, John F. Capman, Frederick L. Oswald, Evan R. Theys, David L. Tomczak

Personnel Assessment and Decisions

Artificial intelligence (AI) and machine learning (ML) have seen widespread adoption by organizations seeking to identify and hire high-quality job applicants. Yet the volume, variety, and velocity of professional involvement among I-O psychologists remains relatively limited when it comes to developing and evaluating AI/ML applications for talent assessment and selection. Furthermore, there is a paucity of empirical research that investigates the reliability, validity, and fairness of AI/ML tools in organizational contexts. To stimulate future involvement and research, we share our review and perspective on the current state of AI/ML in talent assessment as well as its benefits and potential pitfalls; …

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Virtual Wrap-Up Presentation: Digital Libraries, Intelligent Data Analytics, And Augmented Description, Elizabeth Lorang, Leen-Kiat Soh, Yi Liu, Chulwoo Pack Nov 2019

Virtual Wrap-Up Presentation: Digital Libraries, Intelligent Data Analytics, And Augmented Description, Elizabeth Lorang, Leen-Kiat Soh, Yi Liu, Chulwoo Pack

School of Computing: Conference and Workshop Papers

Includes framing, overview, and discussion of the explorations pursued as part of the Digital Libraries, Intelligent Data Analytics, and Augmented Description demonstration project, pursued by members of the Aida digital libraries research team at the University of Nebraska-Lincoln through a research services contract with the Library of Congress. This presentation covered: Aida research team and background for the demonstration project; broad outlines of “Digital Libraries, Intelligent Data Analytics, and Augmented Description”; what changed for us as a research team over the collaboration and why; deliverables of our work; thoughts toward “What next”; and deep-dives into the explorations. The machine learning …

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What Do You Mean? Research In The Age Of Machines, Arthur J. Boston Nov 2019

What Do You Mean? Research In The Age Of Machines, Arthur J. Boston

Faculty & Staff Research and Creative Activity

What Do You Mean?” was an undeniable bop of its era in which Justin Bieber explores the ambiguities of romantic communication. (I pinky promise this will soon make sense for scholarly communication librarians interested in artificial intelligence [AI].) When the single hit airwaves in 2015, there was a meta-debate over what Bieber meant to add to public discourse with lyrics like “What do you mean? Oh, oh, when you nod your head yes, but you wanna say no.” It is unlikely Bieber had consent culture in mind, but the failure of his songwriting team to take into account that some …

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Predicting Audience Engagement Across Social Media Platforms In The News Domain, Kholoud Khalil Aldous, Jisun An, Bernard J. Jansen Nov 2019

Predicting Audience Engagement Across Social Media Platforms In The News Domain, Kholoud Khalil Aldous, Jisun An, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

We analyze cross-platform factors for posts on both single and multiple social media platforms for numerous news outlets to better predict audience engagement, precisely the number of likes and comments. We collect 676,779 social media posts from 53 news outlets during eight months on four social media platforms (Facebook, Instagram, Twitter, and YouTube), along with the associated comments (more than 31 million) and the number of likes (more than 840 million). We develop a framework for predicting the audience engagement based on both linguistic features of the post and social media platform factors. Among other findings, results show that content …

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Artificial Intelligence, Real Impact, Singapore Management University Oct 2019

Artificial Intelligence, Real Impact, Singapore Management University

Perspectives@SMU

AI use in China continues to push innovation envelopes, but technology must be utilised and updated with expert advice

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Designing Women: Essentializing Femininity In Ai Linguistics, Ellianie S. Vega Oct 2019

Designing Women: Essentializing Femininity In Ai Linguistics, Ellianie S. Vega

Student Publications

Since the eighties, feminists have considered technology a force capable of subverting sexism because of technology’s ability to produce unbiased logic. Most famously, Donna Haraway’s “A Cyborg Manifesto” posits that the cyborg has the inherent capability to transcend gender because of its removal from social construct and lack of loyalty to the natural world. But while humanoids and artificial intelligence have been imagined as inherently subversive to gender, current artificial intelligence perpetuates gender divides in labor and language as their programmers imbue them with traits considered “feminine.” A majority of 21st century AI and humanoids are programmed to fit female …

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Technical Report 2019-01: Pupil Labs Eye Tracking User Guide, Joan D. Gannon, Augustine Ubah, Chris Dancy Sep 2019

Technical Report 2019-01: Pupil Labs Eye Tracking User Guide, Joan D. Gannon, Augustine Ubah, Chris Dancy

Other Faculty Research and Publications

No abstract provided.

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Do It Like A Syntactician: Using Binary Gramaticality Judgements To Train Sentence Encoders And Assess Their Sensitivity To Syntactic Structure, Pablo Gonzalez Martinez Sep 2019

Do It Like A Syntactician: Using Binary Gramaticality Judgements To Train Sentence Encoders And Assess Their Sensitivity To Syntactic Structure, Pablo Gonzalez Martinez

Dissertations, Theses, and Capstone Projects

The binary nature of grammaticality judgments and their use to access the structure of syntax are a staple of modern linguistics. However, computational models of natural language rarely make use of grammaticality in their training or application. Furthermore, developments in modern neural NLP have produced a myriad of methods that push the baselines in many complex tasks, but those methods are typically not evaluated from a linguistic perspective. In this dissertation I use grammaticality judgements with artificially generated ungrammatical sentences to assess the performance of several neural encoders and propose them as a suitable training target to make models learn …

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Study On The Development Of Mass Based On Safety, Qiyu Yu Aug 2019

Study On The Development Of Mass Based On Safety, Qiyu Yu

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.

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Document Images And Machine Learning: A Collaboratory Between The Library Of Congress And The Image Analysis For Archival Discovery (Aida) Lab At The University Of Nebraska, Lincoln, Ne, Yi Liu, Chulwoo Pack, Leen-Kiat Soh, Elizabeth Lorang Aug 2019

Document Images And Machine Learning: A Collaboratory Between The Library Of Congress And The Image Analysis For Archival Discovery (Aida) Lab At The University Of Nebraska, Lincoln, Ne, Yi Liu, Chulwoo Pack, Leen-Kiat Soh, Elizabeth Lorang

School of Computing: Conference and Workshop Papers

This presentation summarized and presented preliminary results from the first weeks of work conducted by the Aida research team in response to Library of Congress funding notice ID 030ADV19Q0274, “The Library of Congress – Pre-processing Pilot.” It includes overviews of projects on historic document segmentation, document classification, document quality assessment, figure and graph extraction from historic documents, text-line extraction from figures, subject and objective quality assesments, and digitization type differentiation.

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A Multimodal Approach To Sarcasm Detection On Social Media, Dipto Das Aug 2019

A Multimodal Approach To Sarcasm Detection On Social Media, Dipto Das

Graduate Theses/Dissertations

In recent times, a major share of human communication takes place online. The main reason being the ease of communication on social networking sites (SNSs). Due to the variety and large number of users, SNSs have drawn the attention of the computer science (CS) community, particularly the affective computing (also known as emotional AI), information retrieval, natural language processing, and data mining groups. Researchers are trying to make computers understand the nuances of human communication including sentiment and sarcasm. Emotion or sentiment detection requires more insights about the communication than it does for factual information retrieval. Sarcasm detection is particularly …

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Law Library Blog (August 2019): Legal Beagle's Blog Archive, Roger Williams University School Of Law Aug 2019

Law Library Blog (August 2019): Legal Beagle's Blog Archive, Roger Williams University School Of Law

Law Library Newsletters/Blog

No abstract provided.

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Synthetic, Yet Natural: Properties Of Wordnet Random Walk Corpora And The Impact Of Rare Words On Embedding Performance, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher Jul 2019

Synthetic, Yet Natural: Properties Of Wordnet Random Walk Corpora And The Impact Of Rare Words On Embedding Performance, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher

Conference papers

Creating word embeddings that reflect semantic relationships encoded in lexical knowledge resources is an open challenge. One approach is to use a random walk over a knowledge graph to generate a pseudo-corpus and use this corpus to train embeddings. However, the effect of the shape of the knowledge graph on the generated pseudo-corpora, and on the resulting word embeddings, has not been studied. To explore this, we use English WordNet, constrained to the taxonomic (tree-like) portion of the graph, as a case study. We investigate the properties of the generated pseudo-corpora, and their impact on the resulting embeddings. We find …

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Zac: A Zone Path Construction Approach For Effective Real-Time Ridesharing, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet Jul 2019

Zac: A Zone Path Construction Approach For Effective Real-Time Ridesharing, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet

Research Collection School Of Computing and Information Systems

Real-time ridesharing systems such as UberPool, Lyft Line, GrabShare have become hugely popular as they reduce the costs for customers, improve per trip revenue for drivers and reduce traffic on the roads by grouping customers with similar itineraries. The key challenge in these systems is to group the right requests to travel in available vehicles in real-time, so that the objective (e.g., requests served, revenue or delay) is optimized. The most relevant existing work has focussed on generating as many relevant feasible (with respect to available delay for customers) combinations of requests (referred to as trips) as possible in real-time. …

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Developing Algorithms To Detect Incidents On Freeways From Loop Detector And Vehicle Re-Identification Data, Biraj Adhikari Jul 2019

Developing Algorithms To Detect Incidents On Freeways From Loop Detector And Vehicle Re-Identification Data, Biraj Adhikari

Civil & Environmental Engineering Theses & Dissertations

A new approach for testing incident detection algorithms has been developed and is presented in this thesis. Two new algorithms were developed and tested taking California #7, which is the most widely used algorithm to date, and SVM (Support Vector Machine), which is considered one of the best performing classifiers, as the baseline for comparisons. Algorithm #B in this study uses data from Vehicle Re-Identification whereas the other three algorithms (California #7, SVM and Algorithm #A) use data from a double loop detector for detection of an incident. A microscopic traffic simulator is used for modeling three types of incident …

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